Pragmatic Content in Global and Local ELT Textbooks

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Hussein Meihami

2015-11-01

Full Text Available This study is an attempt to explore the frequency of pragmatic content occurrence represented as three speech acts of requesting, refusing, and apologizing in global and local English Language Teaching (ELT textbooks. Three global elementary ELT textbooks, namely Interchange, Top Notch, and American English File along with the local elementary textbooks of Iran Language Institute (ILI Series, were examined for their pragmatic content. To analyze the pragmatic content of these textbooks, the researchers used three different frameworks. The results indicated that while both global and local ELT textbooks shared a sufficient number of speech acts of request and refusal, they failed to pay enough attention to the speech act of apology regarding its frequency and the strategies through which it is performed. To sum, the findings of this study highlight the differences in the frequency of different speech acts and the strategies used to perform them in global and local elementary ELT textbooks, which bear some implications for ELT textbook developers and language instructors.

Prototyping the E-ELT M1 local control system communication infrastructure

Science.gov (United States)

Argomedo, J.; Kornweibel, N.; Grudzien, T.; Dimmler, M.; Andolfato, L.; Barriga, P.

2016-08-01

The primary mirror of the E-ELT is composed of 798 hexagonal segments of about 1.45 meters across. Each segment can be moved in piston and tip-tilt using three position actuators. Inductive edge sensors are used to provide feedback for global reconstruction of the mirror shape. The E-ELT M1 Local Control System will provide a deterministic infrastructure for collecting edge sensor and actuators readings and distribute the new position actuators references while at the same time providing failure detection, isolation and notification, synchronization, monitoring and configuration management. The present paper describes the prototyping activities carried out to verify the feasibility of the E-ELT M1 local control system communication architecture design and assess its performance and potential limitations.

E-ELT M1 test facility

Science.gov (United States)

Dimmler, M.; Marrero, J.; Leveque, S.; Barriga, P.; Sedghi, B.; Mueller, M.

2012-09-01

During the advanced design phase of the European Extremely Large Telescope (E-ELT) several critical components have been prototyped. During the last year some of them have been tested in dedicated test stands. In particular, a representative section of the E-ELT primary mirror has been assembled with 2 active and 2 passive segments. This test stand is equipped with complete prototype segment subunits, i.e. including support mechanisms, glass segments, edge sensors, position actuators as well as additional metrology for monitoring. The purpose is to test various procedures such as calibration, alignment and handling and to study control strategies. In addition the achievable component and subsystem performances are evaluated, and interface issues are identified. In this paper an overview of the activities related to the E-ELT M1 Test Facility will be given. Experiences and test results are presented.

MICADO: first light imager for the E-ELT

NARCIS (Netherlands)

Davies, R.; Schubert, J.; Hartl, M.; Alves, J.; Clénet, Y.; Lang-Bardl, F.; Nicklas, H.; Pott, J. -U; Ragazzoni, R.; Tolstoy, E.; Agocs, T.; Anwand-Heerwart, H.; Barboza, S.; Baudoz, P.; Bender, R.; Bizenberger, P.; Boccaletti, A.; Boland, W.; Bonifacio, P.; Briegel, F.; Buey, T.; Chapron, F.; Cohen, M.; Czoske, O.; Dreizler, S.; Falomo, R.; Feautrier, P.; Förster Schreiber, N.; Gendron, E.; Genzel, R.; Glück, M.; Gratadour, D.; Greimel, R.; Grupp, F.; Häuser, M.; Haug, M.; Hennawi, J.; Hess, H. J.; Hörmann, V.; Hofferbert, R.; Hopp, U.; Hubert, Z.; Ives, D.; Kausch, W.; Kerber, F.; Kravcar, H.; Kuijken, K.; Leitzinger, M.; Leschinski, K.; Massari, D.; Mei, S.; Merlin, F.; Mohr, L.; Monna, A.; Müller, F.; Navarro, R.; Plattner, M.; Przybilla, N.; Ramlau, R.; Ramsay, S.; Ratzka, T.; Rhode, P.; Richter, J.; Rix, H. -W; Rodeghiero, G.; Rohloff, R. -R; Rousset, G.; Ruddenklau, R.; Schaffenroth, V.; Schlichter, J.; Sevin, A.; Stuik, R.; Sturm, E.; Thomas, J.; Tromp, N.; Turatto, M.; Verdoes-Kleijn, G.; Vidal, F.; Wagner, R.; Wegner, M.; Zeilinger, W.; Ziegler, B.; Zins, G.

2016-01-01

MICADO will equip the E-ELT with a first light capability for diffraction limited imaging at near-infrared wavelengths. The instrument's observing modes focus on various flavours of imaging, including astrometric, high contrast, and time resolved. There is also a single object spectroscopic mode

Leading Role of Educators in ELT for Young Learners

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Jiali Du

2014-10-01

Full Text Available This paper discusses the leading role of Chinese educators in ELT for young learners. English is a global language. ELT for children becomes especially popular in China when English was officially considered compulsory at primary school in 2001. National identity is the presentation of cultural identity, and alien culture helps children understand native culture from the outside perspective. Culture sensitive applications are required to be made in ELT by teachers. Educators’ excellent presentation and students’ well-established practice lead to full production, bringing the active intake from the passive input.

Literature Teaching in ELT

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

To show the importance of literature teaching in English language teaching (ELT),this paper explores the relations between language, culture and literature,examines the present problems in literature teaching and possible solutions are suggested as well.

A Role for Soft Systems Methodology in ELT Projects.

Science.gov (United States)

Holliday, Adrian

1990-01-01

Discusses the uses for soft systems methodology (SSM) in English language training (ELT) projects. It is suggested that ethnographic techniques may help in achieving the understanding needed to start an ELT project while SSM may provide a useful means for structuring ethnographic findings. (Author/VWL)

A Thorough Scrutiny of ELT Textbook Evaluations: A Review Inquiry

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Reza Gholami

2017-07-01

Full Text Available It is thoroughly agreed that English language textbooks stand amongst the foremost components in any language classrooms worldwide, being referred to as valid, beneficial and labor-saving tools to fulfill an extensive range of needs. An ELT textbook is not merely a set of sheets of paper fastened together to hinge at one side, but is the beating heart of any education system whereupon the whole learning revolves. Notwithstanding their interminable benefits, it is admitted that still the compiled textbooks, especially the ones prescribed in Educational systems have to be evaluated and assessed to confirm whether they fulfil the objectives they are meant for or not, as it is said no perfect textbook exists. Having dealt with evaluation in general, this research meticulously elaborates on textbook evaluation more specifically concluding that there is a dearth of inquiry on textbook selection and evaluation. Afterwards, this research introduces the most common approaches for evaluating ELT textbooks and materials. The paper culminates with concluding remarks and implications, hoping to shed light on how textbook evaluation is practiced worldwide.

Applied ELT: A Paradigm Justifying Complex Adaptive System of Language Teaching?

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Masoud Mahmoodzadeh

2013-12-01

Full Text Available In an endeavor to reflect on the advent of Applied ELT paradigm pioneered by Pishghadam (2011 in the area of second language education, this article delves into the unexplored nature of this emerging paradigm via a contemporary complexity-driven voice. The crux of the argument addressed in this article suggests that Applied ELT is a pragmatic manifestation of complex adaptive system of language teaching. To set the grounds expressly for such enquiry, firstly it draws on both premises and axioms associated with complexity theory and its existing literature in the circle of second language research. It then tracks down the evolutionary course of the new developed paradigm of Applied ELT within the realm of second language education and also elaborates the cornerstone and manifold tenets of this paradigm sufficiently. Finally, the article attempts to critically elucidate and rationalize the recent emergence of Applied ELT paradigm through the lens of complexity theory. To broaden our thinking and understanding about the potential and multi-directional influence of ELT field, the article ends by calling for a reshaped educational direction for ELT position in second language education.

Science Data Management for the E-ELT: usecase MICADO

NARCIS (Netherlands)

Verdoes Kleijn, Gijs

2015-01-01

The E-ELT First-light instrument MICADO will explore new parameter space in terms of precision astrometry, photometry and spectroscopy. This provides challenges for the data handling and reduction to ensure MICADO takes the observational capabilities of the AO-assisted E-ELT towards its limits. Our

AN EVALUATION OF SELECTED MOROCCAN ELT TEXTBOOKS: A STANDARDS-BASED APPROACH PERSPECTIVE

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Hassan Ait Bouzid

2017-05-01

Full Text Available Standards-Based Approach to textbook evaluation has been blooming in recent decades. Nevertheless, this practice has received very little attention in Morocco.  The present study aims to bridge a gap in the literature of the Moroccan context by investigating the extent to which three locally designed ELT textbooks conform to the theoretical principles of the Standards-Based Approach which defines the teaching of English as a foreign language in the country (Ministry of National Education, 2007. Its objective is to examine whether and how these textbooks present contents that enable learners to meet the content standards included in the goal areas of Communications, Cultures, Connections and Comparisons. The study is informed by the theoretical framework of the Standards-Based Approach. It adopts a mixed-methods design that uses content analysis as a mixed data analysis method combining both quantitative and qualitative techniques. The findings reveal a number of shortcomings relevant to the representation of the content standards as several standards are not sufficiently addressed in the activities included in these textbooks. Eventually, some suggestions are addressed to policy makers, textbook designers and teachers to overcome the identified problems in current and future textbooks. The study is expected to sensitize ELT practitioners about the viability of using textbook evaluation in boosting both the quality of ELT textbooks and the quality of the teaching learning outcomes.

Simulating a Direction-Finder Search for an ELT

Science.gov (United States)

Bream, Bruce

2005-01-01

A computer program simulates the operation of direction-finding equipment engaged in a search for an emergency locator transmitter (ELT) aboard an aircraft that has crashed. The simulated equipment is patterned after the equipment used by the Civil Air Patrol to search for missing aircraft. The program is designed to be used for training in radio direction-finding and/or searching for missing aircraft without incurring the expense and risk of using real aircraft and ground search resources. The program places a hidden ELT on a map and enables the user to search for the location of the ELT by moving a 14 NASA Tech Briefs, March 2005 small aircraft image around the map while observing signal-strength and direction readings on a simulated direction- finding locator instrument. As the simulated aircraft is turned and moved on the map, the program updates the readings on the direction-finding instrument to reflect the current position and heading of the aircraft relative to the location of the ELT. The software is distributed in a zip file that contains an installation program. The software runs on the Microsoft Windows 9x, NT, and XP operating systems.

Intelligent vibration control of ELTs and large AO hardware

Science.gov (United States)

Pott, J.-U.; Kürster, M.; Trowitzsch, J.; Borelli, J.; Rohloff, R.-R.; Herbst, T.; Böhm, M.; Keck, A.; Ruppel, T.; Sawodny, O.

2012-07-01

MPIA leads the construction of the LINC-NIRVANA instrument, the MCAO-supported Fizeau imager for the LBT, serves as pathfinder for future ELT-AO imagers in terms of size and technology. In this contribution, we review recent results and significant progress made on the development of key items of our stratgey to achieve a piston stability of up to 100nm during a science exposure. We present an overview of our vibration control strategies for optical path and tip-tilt stabilization, involving accelerometer based real-time vibration measurements, vibration sensitive active control of actuators, and the development of a dynamical model of the LBT. MPIA also co-develops the E-ELT first-light NIR imager MICADO (both SCAO and MCAO assisted). Our experiences, made with LINC-NIRVANA, will be fed into the MICADO structural AO design to reach highest on-sky sensitivity.

High-precision astrometry towards ELTs

NARCIS (Netherlands)

Massari, Davide; Fiorentino, Giuliana; Tolstoy, Eline; McConnachie, Alan; Stuik, Remko; Schreiber, Laura; Andersen, David; Clénet, Yann; Davies, Richard; Gratadour, Damien; Kuijken, Konrad; Navarro, Ramon; Pott, Jörg-Uwe; Rodeghiero, Gabriele; Turri, Paolo; Verdoes Kleijn, Gijs

2016-01-01

With the aim of paving the road for future accurate astrometry with MICADO at the European-ELT, we performed an astrometric study using two different but complementary approaches to investigate two critical components that contribute to the total astrometric accuracy. First, we tested the predicted

The E-ELT program status

Science.gov (United States)

Tamai, Roberto; Cirasuolo, Michele; González, Juan Carlos; Koehler, Bertrand; Tuti, Mauro

2016-07-01

ESO is now fully engaged in building the European Extremely Large Telescope (E-ELT), a 40-m class optical nearinfrared telescope to be installed on top of Cerro Armazones, Chile and become operational around 2025. The Programme was formally approved by ESO Council back in 2012. However the required funding level for starting construction was actually reached in 2014, leading to a Green Light to start large construction contracts in December of that year. Since then, the programme has entered a very busy phase leading to the signature of the first major industrial contracts as well as the agreements with scientific institutes in ESO Member States to design and built the first suite of science instruments. This paper summarizes the current status of the E-ELT Programme and presents some aspects related to scientific objectives, managerial organization, programmatic aspects and system engineering approach. It also outlines the procurement strategies put in place to achieve the goal of the Programme: building the 'world's biggest eye on the sky' within the next decade.

77 FR 1779 - Emergency Locator Transmitters (ELTs)

Science.gov (United States)

2012-01-11

... INFORMATION CONTACT: Mr. Albert Sayadian, AIR-130, Federal Aviation Administration, 470 L'Enfant Plaza, Suite... nautical miles in radius. Additionally, 406 MHz ELTs which have a GPS position input can potentially reduce...

Creativity and innovations in ELT materials development looking beyond the current design

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Bao, Dat

2018-01-01

This book challenges current practices in ELT materials design in order to transform coursebook quality. It proposes ways to improve task design through resources such as drama, poetry, literature and online resources; and it maps out a number of unusual connections between theory and practice in the field of ELT materials development.

Reflections on practicum experiences of non-ELT student teachers in Turkey

OpenAIRE

Mirici, İsmail Hakkı; Ölmez-Çağlar, Funda

2018-01-01

In English language teacher education (hereafter ELT)programs of Turkish universities, teaching practicum has a critical value dueto its pivotal role in equipping student teachers with the necessarycompetences and preparing them for the teaching profession. Practicumexperience turns out to be of greater importance for the graduates of otherEnglish language departments (hereafter non-ELT) such as English Linguistics,English Language and Literature or American Culture and Literature who attendp...

VIEW FROM THE TOP: ENJOYABLE AND EFFECTIVE APPROACHES TO ELT FOR FLIGHT ATTENDANT

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Nanik Rianandita Sari,S.S.,M.A.

2017-04-01

Full Text Available Young people today are more exposed to popular culture than any other age group. Television, movies, music, magazines, fashion, and internet form a major psychological part of the lives and life styles of youngsters. Since there has been increasing interest in the use of popular culture as aids in learning English. This research will investigate the ways in which popular culture might be used in teaching English. Learning language through pop culture, which comes from the West. Music, songs, and movies are highly popular with youngster. The movie ‘View From The Top‘, in particular, was a popular movie, where it entered the fantasy world of most young girl who want to be a flight attendant class of 2011. Many of flight attendant watch this movie for several times, remembering the lines spoken by the actress, and reciting the lyrics of the theme songs. All of which seems to suggest that flight attendant student can learn English through their encounters with popular culture. A movie is one interesting way to learn English. Movie is one of popular culture which is part of oral literature which enhances ELT through elements such as authentic material, language in use and aesthetic representation of the spoken language, as well as language and cultural enrichment. Literature appeals to flight attendant students, it motivates them to become responsive and active learners.

Beyond the didactic classroom: educational models to encourage active student involvement in learning.

Science.gov (United States)

Shreeve, Michael W

2008-01-01

In a chiropractic college that utilizes a hybrid curriculum model composed of adult-based learning strategies along with traditional lecture-based course delivery, a literature search for educational delivery methods that would integrate the affective domain and the cognitive domain of learning provided some insights into the use of problem-based learning (PBL), experiential learning theory (ELT), and the emerging use of appreciative inquiry (AI) to enhance the learning experience. The purpose of this literature review is to provide a brief overview of key components of PBL, ELT, and AI in educational methodology and to discuss how these might be used within the chiropractic curriculum to supplement traditional didactic lecture courses. A growing body of literature describes the use of PBL and ELT in educational settings across many disciplines, both at the undergraduate and graduate levels. The use of appreciative inquiry as an instructional methodology presents a new area for exploration and study in the academic environment. Educational research in the chiropractic classroom incorporating ELT and appreciative inquiry might provide some valuable insights for future curriculum development.

Exploring ELT Students’ Perception of Mobile Phone through Figurative Language

OpenAIRE

ŞENEL, Müfit

2016-01-01

The aim of this study is to investigate, analyze and evaluate the mobile phone perceptions of ELT students by the help of figurative language. The participants of this study are Grade 3 and Grade 4 students of ELT Department at Samsun 19 Mayıs University, Faculty of Education, involving 139 students in total. In this research students were asked to use “simile” as a figurative language and complete the sentence “Mobile phone is as ……as…….”  in the target language.  According to content analys...

Endoderm development in Caenorhabditis elegans: the synergistic action of ELT-2 and -7 mediates the specification→differentiation transition.

Science.gov (United States)

Sommermann, Erica M; Strohmaier, Keith R; Maduro, Morris F; Rothman, Joel H

2010-11-01

The transition from specification of cell identity to the differentiation of cells into an appropriate and enduring state is critical to the development of embryos. Transcriptional profiling in Caenorhabditis elegans has revealed a large number of genes that are expressed in the fully differentiated intestine; however, no regulatory factor has been found to be essential to initiate their expression once the endoderm has been specified. These gut-expressed genes possess a preponderance of GATA factor binding sites and one GATA factor, ELT-2, fulfills the expected characteristics of a key regulator of these genes based on its persistent expression exclusively in the developing and differentiated intestine and its ability to bind these regulatory sites. However, a striking characteristic of elt-2(0) knockout mutants is that while they die shortly after hatching owing to an obstructed gut passage, they nevertheless contain a gut that has undergone complete morphological differentiation. We have discovered a second gut-specific GATA factor, ELT-7, that profoundly synergizes with ELT-2 to create a transcriptional switch essential for gut cell differentiation. ELT-7 is first expressed in the early endoderm lineage and, when expressed ectopically, is sufficient to activate gut differentiation in nonendodermal progenitors. elt-7 is transcriptionally activated by the redundant endoderm-specifying factors END-1 and -3, and its product in turn activates both its own expression and that of elt-2, constituting an apparent positive feedback system. While elt-7 loss-of-function mutants lack a discernible phenotype, simultaneous loss of both elt-7 and elt-2 results in a striking all-or-none block to morphological differentiation of groups of gut cells with a region-specific bias, as well as reduced or abolished gut-specific expression of a number of terminal differentiation genes. ELT-2 and -7 synergize not only in activation of gene expression but also in repression of a gene that

Is there ELF in ELT coursebooks?

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Paola Vettorel

2013-10-01

Full Text Available This article aims to explore whether well-attested findings in the fields of World Englishes (WE and of English as a lingua franca (ELF have determined a shift in perspective in the overall approach to English language teaching (ELT, and how far this shift has permeated teaching materials and coursebooks. The research study was carried out in Italy, a country where ELT coursebooks have often played a relevant role in introducing innovations in language teaching methodology. The research design included a corpus of ten coursebooks that have been published and adopted in Italian secondary schools in the last 6 years. The coursebooks were evaluated in terms of the presence or absence of references to WE and/or ELF, of awareness-raising activities, of the promotion of using English outside the school environment and of the use of effective English communication and intercultural strategies among nonnative speakers. Findings show that there have been no significant changes in the inclusion of WE- and ELForiented materials and related tasks, apart from the area of promotion of cultural and intercultural awareness.

What is the Place of English Literature in ELT Classrooms? A Review of Related Studies

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Tarek A. Alkhaleefah

2017-10-01

Full Text Available The debate over the place and role of literature in language classrooms has long intrigued researchers and teachers’ interests over the years. Although there is an overall consensus that the teaching of literature in English language teaching (ELT classrooms can help foster L2 learners’ language skills and cognitive abilities, some researchers have suggested that integrating literature in ELT classrooms should be approached with caution due to EFL learners’ limited language proficiency. In this paper, the researcher reviews previous related studies on the place of literature in the English language teaching (ELT contexts. The aim of this review is to shed light on this researchers/teachers’ ongoing debate over the place of teaching English literature in ELT. In particular, the review examines how researchers perceive the role of literature and its authenticity in ELT classrooms as stimulating learners’ interests and personal engagement with literary texts, fostering L2 learners’ language skills (particularly their reading and creative writing skills, and enhancing their critical thinking skills and strategic processing of texts. Furthermore, the review covers issues related to how the integration of literature in language classrooms should be carefully task-designed and assessed.

SKILLS-BASED ECLECTIC TECHNIQUES MATRIX FOR ELT MICROTEACHINGS

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İskender Hakkı Sarıgöz

2016-10-01

Full Text Available Foreign language teaching undergoes constant changes due to the methodological improvement. This progress may be examined in two parts. They are the methods era and the post-methods era. It is not pragmatic today to propose a particular language teaching method and its techniques for all purposes. The holistic inflexibility of mid-century methods has long gone. In the present day, constructivist foreign language teaching trends attempt to see the learner as a whole person and an individual who may be different from the other students in many respects. At the same time, the individual differences should not keep the learners away from group harmony. For this reason, current teacher training programs require eclectic teaching matrixes for unit design considering the mixed ability student groups. These matrixes can be prepared in a multidimensional fashion because there are many functional techniques in different methods and other new techniques to be created by instructors freely in accordance with the teaching aims. The hypothesis in this argument is that the collection of foreign language teaching techniques compiled in ELT microteachings for a particular group of learners has to be arranged eclectically in order to update the teaching process. Nevertheless, designing a teaching format of this sort is a demanding and highly criticized task. This study briefly argues eclecticism in language-skills based methodological struggle from the perspective of ELT teacher education.

Posters, Self-Directed Learning, and L2 Vocabulary Acquisition

Science.gov (United States)

Cetin, Yakup; Flamand, Lee

2013-01-01

Posters, either as promotions by various ELT publishing houses or prepared by ELT teachers and students, are widely used on the walls of many foreign language classrooms. Many of them consist of colourful pictures along with L2 vocabulary, grammar, and texts in order to contribute to the foreign language learning process. However, many ELT…

Examining the Perceptions of English Instructors Regarding the Incorporation of Global Citizenship Education into ELT

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Fatma BAŞARIR

2017-12-01

Full Text Available The aim of this study is to explore the perceptions of ELT instructors working at a higher education institution in Turkey regarding integrating global citizenship education into ELT courses. The study was carried out by using phenomenological design, which is one of the qualitative studies. The data were collected using interview method and a semi-structured interview form was developed by the researcher as the data collection tool. The participants, selected on the basis of easily accessible sampling method, which is one of the purposeful sampling methods. The participants comprises of 13 English instructors who work at a higher education institution in the Central Anatolia Region in the academic year 2015-2016. Instructors’ opinions were taken regarding how they described global citizenship, what were their roles and responsibilities in educating students as global citizens, how they practiced global citizenship education in their classes, and the challenges they were facing in practicing global citizenship education in ELT courses. Data were analysed with content analysis technique. Findings revealed that participants mostly focused on the “value” dimension of global citizenship such as respect, sensitivity, sense of belonging, responsibility, openness, etc. The instructors deemed their roles and responsibilities in preparing students as global citizens as an informer and role model. While most of the participants stated that they did not involve any specific teaching practices in their classes to educate students as global citizens, as they thought ELT lessons and global citizenship education were irrelevant, addressing global issues in the courses and role modelling were conducted by few instructors to promote global citizenship. Predominantly grammar-based teaching and student unwillingness were found as challenges of integrating global citizenship into ELT. As a result, it was concluded that ELT instructors have insufficient levels

China English and ELT for English Majors

Science.gov (United States)

Zhang, Mingjuan

2008-01-01

This paper is a general study of one of varieties of English--China English and its influence on English Language Teaching (ELT) for English majors. The status of English as an International language breaks the situation in which British English or American English is the sole standard. English becomes World Englishes, taking on a plural form,…

The ELT in 2017: The Year of the Primary Mirror

Science.gov (United States)

Cirasuolo, M.; Tamai, R.; Cayrel, M.; Koehler, B.; Biancat Marchet, F..; González, J. C.; Dimmler, M.; Tuti, M.; ELT Team

2018-03-01

The Extremely Large Telescope (ELT) is at the core of ESO's vision to deliver the largest optical and infrared telescope in the world. With its unrivalled sensitivity and angular resolution the ELT will transform our view of the Universe: from exoplanets to resolved stellar populations, from galaxy evolution to cosmology and fundamental physics. This article focuses on one of the most challenging aspects of the entire programme, the 39-metre primary mirror (M1). 2017 was a particularly intense year for M1, the main highlight being the approval by ESO's Council to proceed with construction of the entire mirror. In addition, several contracts have been placed to ensure that the giant primary mirror will be operational at first light.

Teacher as Learning Facilitator in ELT

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Badea Elena Codruta

2012-05-01

Full Text Available The classroom is the magic active scenery where many educational things take place simultaneously.Intellectual, emotional, socio-cultural, motivational and curricular factors corroborate their influence onclassroom environments, whether we deal with traditional models of teaching or with the constructivistapproaches. The growing demand for language teachers, English in particular, has determined a new vision oflanguage teaching strategies. The cutting-edge technology has created a fertile ground which successfullyfosters the teacher –student communication, emphasizing the teacher’s role to guide students and to generate achange in their learning approach and in eliciting useable knowledge. This way, the teacher has a larger abilityto convert knowledge into practical information that is of real help and value to students. Students are involvedin a continuous educational scheme and are tested on what they have learned. This ensures they can alwaysenjoy the benefits of active learning from expert teachers. The present paper deals with a brief analysis of therole of teacher as learning facilitator and its importance for student acquisition process, eliciting some strategiesin support of collaborative and student-centered learning.

Moving and Learning: Expanding Style and Increasing Flexibility

Science.gov (United States)

Peterson, Kay; DeCato, Lisa; Kolb, David A.

2015-01-01

This article introduces ways in which movement can enhance one's understanding of how to learn using Experiential Learning Theory (ELT) concepts of the Learning Cycle, Learning Styles, and Learning Flexibility. The theoretical correspondence between the dialectic dimensions of the Learning Cycle and the dimensions of the Laban Movement Analysis…

E-ELT constraints on runaway dilaton scenarios

Energy Technology Data Exchange (ETDEWEB)

Martinelli, M. [Institut für Theoretische Physik, Ruprecht-Karls-Universität Heidelberg, Philosophenweg 16, 69120, Heidelberg (Germany); Calabrese, E. [Sub-department of Astrophysics, University of Oxford, Keble Road, Oxford OX1 3RH (United Kingdom); Martins, C.J.A.P., E-mail: m.martinelli@thphys.uni-heidelberg.de, E-mail: erminia.calabrese@physics.ox.ac.uk, E-mail: carlos.martins@astro.up.pt [Centro de Astrofìsica, Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal)

2015-11-01

We use a combination of simulated cosmological probes and astrophysical tests of the stability of the fine-structure constant α, as expected from the forthcoming European Extremely Large Telescope (E-ELT), to constrain the class of string-inspired runaway dilaton models of Damour, Piazza and Veneziano. We consider three different scenarios for the dark sector couplings in the model and discuss the observational differences between them. We improve previously existing analyses investigating in detail the degeneracies between the parameters ruling the coupling of the dilaton field to the other components of the universe, and studying how the constraints on these parameters change for different fiducial cosmologies. We find that if the couplings are small (e.g., α{sub b} = α{sub V} ∼ 0) these degeneracies strongly affect the constraining power of future data, while if they are sufficiently large (e.g., α{sub b} ∼> 10{sup −5}−α{sub V} ∼> 0.05, as in agreement with current constraints) the degeneracies can be partially broken. We show that E-ELT will be able to probe some of this additional parameter space.

Assessing learning styles of Saudi dental students using Kolb's Learning Style Inventory.

Science.gov (United States)

ALQahtani, Dalal A; Al-Gahtani, Sara M

2014-06-01

Experiential learning theory (ELT), a theory developed by David Kolb that considers experience to be very important for learning, classifies learners into four categories: Divergers, Assimilators, Convergers, and Accommodators. Kolb used his Learning Style Inventory (LSI) to validate ELT. Knowing the learning styles of students facilitates their understanding of themselves and thereby increases teaching efficiency. Few studies have been conducted that investigate learning preferences of students in the field of dentistry. This study was designed to distinguish learning styles among Saudi dental students and interns utilizing Kolb's LSI. The survey had a response rate of 62 percent (424 of 685 dental students), but surveys with incomplete answers or errors were excluded, resulting in 291 usable surveys (42 percent of the student population). The independent variables of this study were gender, clinical experience level, academic achievement as measured by grade point average (GPA), and specialty interest. The Diverging learning style was the dominant style among those in the sample. While the students preferred the Assimilating style during their early preclinical years, they preferred the Diverging style during their later clinical years. No associations were found between students' learning style and their gender, GPA, or specialty interest. Further research is needed to support these findings and demonstrate the impact of learning styles on dental students' learning.

The Effects of Embedding Information Technologies within ELT on EFL Learners’ Motivation and Interest

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Shaker Al-Mohammadi

2014-01-01

Full Text Available In today’s globalised world, technologies have been embedded in every aspect of daily activities and discourses. The field of education made no exception and hence technologies have become an integral part of all educational systems worldwide, but with different levels and layers. The presence of information technology in English language teaching has brought about notable changes for teachers and learners alike. Accordingly, this paper investigates the impact of integrating information technologies in ELT on EFL learners’ motivation and interest. Based on an authentic comparative case study, this paper explores the influence of information technology on EFL learners’ perceptions, motivation, and interest in the context of ELT in the Tunisian higher education. The findings of this study suggest that the integration of IT in ELT heavily affects EFL students’ motivation and academic performance and hence EFL instructors should take this variable into consideration.

Exploring the extent to which ELT students utilise smartphones for ...

African Journals Online (AJOL)

Zehra

2015-11-09

Nov 9, 2015 ... aimed to explore the extent to which English Language Teaching (ELT) students utilise ... Given the fact that almost all students have a personal smartphone, and use it ..... ears as a disadvantage for smartphones (Kétyi,.

77 FR 41473 - Proposed Technical Standard Order (TSO)-C126b, 406 MHz Emergency Locator Transmitters (ELT) and...

Science.gov (United States)

2012-07-13

... to ensure proper retention of ELTs during airplane accidents.'' (2) NTSB Factual Report--Aviation... airplanes. This diversity in mounting techniques include improper and/or inadequate mounting of many ELT's... maintenance instructions for the article are revised to include the following information by June 30, 2013: a...

E-ELT Site Chosen - World's Biggest Eye on the Sky to be Located on Armazones, Chile

Science.gov (United States)

2010-04-01

On 26 April 2010, the ESO Council selected Cerro Armazones as the baseline site for the planned 42-metre European Extremely Large Telescope (E-ELT). Cerro Armazones is a mountain at an altitude of 3060 metres in the central part of Chile's Atacama Desert, some 130 kilometres south of the town of Antofagasta and about 20 kilometres from Cerro Paranal, home of ESO's Very Large Telescope. "This is an important milestone that allows us to finalise the baseline design of this very ambitious project, which will vastly advance astronomical knowledge," says Tim de Zeeuw, ESO's Director General. "I thank the site selection team for the tremendous work they have done over the past few years." ESO's next step is to build a European extremely large optical/infrared telescope (E-ELT) with a primary mirror 42 metres in diameter. The E-ELT will be "the world's biggest eye on the sky" - the only such telescope in the world. ESO is drawing up detailed construction plans together with the community. The E-ELT will address many of the most pressing unsolved questions in astronomy, and may, eventually, revolutionise our perception of the Universe, much as Galileo's telescope did 400 years ago. The final go-ahead for construction is expected at the end of 2010, with the start of operations planned for 2018. The decision on the E-ELT site was taken by the ESO Council, which is the governing body of the Organisation composed of representatives of ESO's fourteen Member States, and is based on an extensive comparative meteorological investigation, which lasted several years. The majority of the data collected during the site selection campaigns will be made public in the course of the year 2010. Various factors needed to be considered in the site selection process. Obviously the "astronomical quality" of the atmosphere, for instance, the number of clear nights, the amount of water vapour, and the "stability" of the atmosphere (also known as seeing) played a crucial role. But other

A profile on the methodology courses at the ELT departments of the education faculties in Turkey

OpenAIRE

Dalkılıç, Nilüfer

1996-01-01

Ankara : Institute of Economics and Social Sciences, Bilkent Univ., 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves 78-80 In this study, the methodology courses at ELT departments in Turkey were examined in terms of design, content and delivery. In order to collect data, sample ELT Departments of the Education Faculties in Turkey were chosen from different parts of Turkey. Data were collected through questionnaires administered to two ...

Electron Technology: ELTE 2016

Science.gov (United States)

Pisarkiewicz, Tadeusz; Kucewicz, Wojciech

2016-12-01

In this paper we present a review of research results and technical accomplishments presented by researchers from technical universities, governmental institutes and research companies during the XIIth Scientific Conference Electron Technology, ELTE 2016. This review is based on materials presented at four topical conference sessions: Microelectronics and Nanoelectronics, Photonics, Materials and Technologies, and Microsystems and also on materials presented by invited speakers at two dedicated sessions. Oral sessions were accompanied by the poster sessions. In effect about 50 papers gathered in this volume reflect the topics discussed at the Conference. A short description of technological and measurement possibilities in the laboratories of Academic Centre for Materials and Nanotechnology and also in the Department of Electronics of the Faculty of Computer Science, Electronics and Telecommunications AGH UST are given.

Digital technology use in ELT classrooms and self-directed learning

OpenAIRE

Nehir Sert; Ebru Boynueğri

2016-01-01

The digital era is a new challenge for teachers. While children get acquainted with digital technology before the age of six, teachers, who have encountered the digital world at a later time in their lives, struggle with it. Self-directed learning, which is crucial for lifelong learning, can be enhanced by the use of technology within and beyond classroom settings. The aim of this study was to examine the difference between the perceptions of students in low- and high-income groups about thei...

Hidden Curriculum: An Analysis of Cultural Content of the ELT Textbooks in Inner, Outer, and Expanding Circle Countries

Science.gov (United States)

Rashidi, Naser; Meihami, Hussein

2016-01-01

Despite the great body of work examining the cultural content of the international and local ELT textbooks, the cultural content and elements of the ELT textbooks in the inner, outer, and expanding circle countries have seldom been reported. That said, the purpose of this study was twofold: first, it was aimed to investigate the cultural content…

Introducing Diversity of English into ELT: Student Teachers' Responses

Science.gov (United States)

Suzuki, Ayako

2011-01-01

The growing use of English by its L2 speakers for their international communication has started to suggest a need for many changes in ELT, particularly in traditional EFL countries. One of the changes discussed among some sociolinguists is the introduction of different varieties of English from the two traditionally highly regarded varieties, i.e.…

INTEGRATING ICT IN ENGLISH LANGUAGE TEACHING AND LEARNING IN INDONESIA

Directory of Open Access Journals (Sweden)

Tuti Hidayati

2016-11-01

Full Text Available Indonesian ELT is complex for numerous reasons, and the level of students‟ outcome has been regarded unsatisfactory by a number of researchers and academics. This paper considers ICT as one of possible alternatives to deal with the complexity of Indonesian ELT and to improve its outcomes. It widely explores ICT integration in English LTL, especially on how ICT has been used in this field. It further investigates the benefits and challenges of integrating ICT in LTL. The paper argues that the integration of ICT is promising for changing and improving the effectiveness of the current Indonesian ELT condition when it is carried out in line with the effective LTL principles. The integration of ICT will enable teachers to vary teaching and learning activities, to gradually change the teaching style to be more student-centred, to train students to have more active role in learning, and to access a huge range of authentic learning materials. The paper also acknowledges the contraints that will emerge in an effort of integrating ICT in Indonesian English LTL. Hence, some recommedations for action are proposed at the end.

Turkish ELT students' willingness to communicate in English

OpenAIRE

Şener, Sabriye

2014-01-01

This paper aims to present the willingness to communicate (WTC) in English of the English Language Teaching Department (ELT) students of Çanakkale Onsekiz Mart University inside and outside the class. Additionally, the relationships among students’ willingness to communicate in English, their linguistic self-confidence, motivation, attitudes toward international community, and personality will be presented. To this end, quantitative data were gathered from 274 students studying at the departm...

The nT1 translocation separates vulval regulatory elements from the egl-18 and elt-6 GATA factor genes.

Science.gov (United States)

Koh, Kyunghee; Bernstein, Yelena; Sundaram, Meera V

2004-03-01

egl-18 and elt-6 are partially redundant, adjacent genes encoding GATA factors essential for viability, seam cell development, and vulval development in Caenorhabditis elegans. The nT1 reciprocal translocation causes a strong Vulvaless phenotype, and an nT1 breakpoint was previously mapped to the left arm of LGIV, where egl-18/elt-6 are located. Here we present evidence that the nT1 vulval phenotype is due to a disruption of egl-18/elt-6 function specifically in the vulva. egl-18 mutations do not complement nT1 for vulval defects, and the nT1 breakpoint on LGIV is located within approximately 800 bp upstream of a potential transcriptional start site of egl-18. In addition, we have identified a approximately 350-bp cis-regulatory region sufficient for vulval expression just upstream of the nT1 breakpoint. By examining the fusion state and division patterns of the cells in the developing vulva of nT1 mutants, we demonstrate that egl-18/elt-6 prevent fusion and promote cell proliferation at multiple steps of vulval development.

Metrology requirements for the serial production of ELT primary mirror segments

Science.gov (United States)

Rees, Paul C. T.; Gray, Caroline

2015-08-01

The manufacture of the next generation of large astronomical telescopes, the extremely large telescopes (ELT), requires the rapid manufacture of greater than 500 1.44m hexagonal segments for the primary mirror of each telescope. Both leading projects, the Thirty Meter Telescope (TMT) and the European Extremely Large Telescope (E-ELT), have set highly demanding technical requirements for each fabricated segment. These technical requirements, when combined with the anticipated construction schedule for each telescope, suggest that more than one optical fabricator will be involved in the delivery of the primary mirror segments in order to meet the project schedule. For one supplier, the technical specification is challenging and requires highly consistent control of metrology in close coordination with the polishing technologies used in order to optimize production rates. For production using multiple suppliers, however the supply chain is structured, consistent control of metrology along the supply chain will be required. This requires a broader pattern of independent verification than is the case of a single supplier. This paper outlines the metrology requirements for a single supplier throughout all stages of the fabrication process. We identify and outline those areas where metrology accuracy and duration have a significant impact on production efficiency. We use the challenging ESO E-ELT technical specification as an example of our treatment, including actual process data. We further develop this model for the case of a supply chain consisting of multiple suppliers. Here, we emphasize the need to control metrology throughout the supply chain in order to optimize net production efficiency.

A Thorough Scrutiny of ELT Textbook Evaluations: A Review Inquiry

Science.gov (United States)

Gholami, Reza; Noordin, Nooreen; Rafik-Galea, Shameem

2017-01-01

It is thoroughly agreed that English language textbooks stand amongst the foremost components in any language classrooms worldwide, being referred to as valid, beneficial and labor-saving tools to fulfill an extensive range of needs. An ELT textbook is not merely a set of sheets of paper fastened together to hinge at one side, but is the beating…

Technology and the Human Dimension: An Interview with Elting E. Morison.

Science.gov (United States)

Bowser, Hal

1985-01-01

Elting E. Morison (a distinguished historian) discusses America's inventive past and ponders how Americans might benefit from understanding it better. The interview elicits his expertise as an interpreter of technology and his beliefs about teaching technology in schools, the role of technology in society, and future prospects. (DH)

ELT-MELAS analyzer and its on-line programs

International Nuclear Information System (INIS)

Anikeev, V.B.; Berezhnoj, V.A.; Glupova

1976-01-01

ELT-MELAS device constructed for an automatic analysis of pictures from big bubble chambers is described. It is controlled by a medium-size ICL-1903A computer and has two measuring modes: analysis of the ''agreement'' signal and digitation of slice-scans. Main features of the hardware and of on-line controlling and diagnostic software are presented. The test results of the MELAS complex as well as preliminary results of the scan-slice measurements of pictures from 15sup(') chamber are given

Nanometre-accurate form measurement machine for E-ELT M1 segments

NARCIS (Netherlands)

Bos, A.; Henselmans, R.; Rosielle, P.C.J.N.; Steinbuch, M.

2015-01-01

To enable important scientific discoveries, ESO has defined a new ground-based telescope: the European Extremely Large Telescope (E-ELT). The baseline design features a telescope with a 39-m-class primary mirror (M1), making it the largest and most powerful telescope in the world. The M1 consists of

The Science Case for Multi-Object Spectroscopy on the European ELT

NARCIS (Netherlands)

Evans, Chris; Puech, Mathieu; Afonso, Jose; Almaini, Omar; Amram, Philippe; Aussel, Hervé; Barbuy, Beatriz; Basden, Alistair; Bastian, Nate; Battaglia, Giuseppina; Biller, Beth; Bonifacio, Piercarlo; Bouché, Nicholas; Bunker, Andy; Caffau, Elisabetta; Charlot, Stephane; Cirasuolo, Michele; Clenet, Yann; Combes, Francoise; Conselice, Chris; Contini, Thierry; Cuby, Jean-Gabriel; Dalton, Gavin; Davies, Ben; de Koter, Alex; Disseau, Karen; Dunlop, Jim; Epinat, Benoît; Fiore, Fabrizio; Feltzing, Sofia; Ferguson, Annette; Flores, Hector; Fontana, Adriano; Fusco, Thierry; Gadotti, Dimitri; Gallazzi, Anna; Gallego, Jesus; Giallongo, Emanuele; Gonçalves, Thiago; Gratadour, Damien; Guenther, Eike; Hammer, Francois; Hill, Vanessa; Huertas-Company, Marc; Ibata, Roridgo; Kaper, Lex; Korn, Andreas; Larsen, Søren; Le Fèvre, Olivier; Lemasle, Bertrand; Maraston, Claudia; Mei, Simona; Mellier, Yannick; Morris, Simon; Östlin, Göran; Paumard, Thibaut; Pello, Roser; Pentericci, Laura; Peroux, Celine; Petitjean, Patrick; Rodrigues, Myriam; Rodríguez-Muñoz, Lucía; Rouan, Daniel; Sana, Hugues; Schaerer, Daniel; Telles, Eduardo; Trager, Scott; Tresse, Laurence; Welikala, Niraj; Zibetti, Stefano; Ziegler, Bodo

2015-01-01

This White Paper presents the scientific motivations for a multi-object spectrograph (MOS) on the European Extremely Large Telescope (E-ELT). The MOS case draws on all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from

Evaluation of Listening Skill of ELT Textbook at Secondary School Level

Directory of Open Access Journals (Sweden)

Mumtaz Ahmed

2015-06-01

Full Text Available Textbook evaluation means development of textbook that is based on rigorous research. In Pakistan text books are designed on communicative language teaching which focuses on communication. Morley (1991 has asserted that listening has a critical role in communication and in language acquisition because the better the students understand, the better they will be able to speak. In our text books, listening practices (text and activities are missing, and listening plays a secondary role as compared to speaking, as it is part of oral work that are dialogues and role play, neglecting that during conversation in English our students face hurdles in quick thinking and accurate predicting because of ignoring listening skill which help in learning sound, rhythm, intonation, pronunciation, vocabulary and grammatical details. The researchers’ intention here is to put different views on importance of listening skill and to evaluate English Text Books prescribed in Punjab government school whether they contain listening material, corresponding activities and related audio video material in text books. Keywords: Evaluation, listening skill, ELT, textbook, Punjab Textbook Board (PTB

Managing Innovation in Language Education: A Course for ELT Change Agents

Science.gov (United States)

Waters, Alan; Vilches, Ma. Luz C.

2005-01-01

As a steady stream of recent papers indicates, ELT curriculum reform projects are not always as successful as they might be. One overall reason for this situation appears to be a failure to adequately take into account concepts and practices from the world of innovation management. This paper describes an attempt to contribute towards ameliorating…

EPISTEMOLOGICAL BELIEFS AND METACOGNITIVE STRATEGIES OF ELT PRE-SERVICE TEACHERS IN DISTANCE AND FORMAL EDUCATION

Directory of Open Access Journals (Sweden)

Meral GUVEN

2012-04-01

Full Text Available The epistemological beliefs in learning process have been investigated from different aspects in relation with many variables in literature. Such beliefs are defined as individuals’ beliefs regarding knowledge and learning. As another related, popular concept, the metacognitive strategies are identified as the strategies used to control the process of obtaining knowledge. Thus, it is seen that both of them are employed to make learning more effective. Within this framework, the aim of the present study was to determine the epistemological beliefs and metacognitive strategies of the pre-service teachers in the distance and formal education English Language Teaching program and to investigate whether there was any difference/ were any differences between them. To collect data, “Epistemological Belief Scale” developed by Schommer (1990 and translated and validated by Deryakulu and Büyüköztürk (2002 and “Metacognitive Strategy Inventory” which was adapted for university students by Yıldız, Akpınar and Ergin (2006 were used. Then through the descriptive method they were analyzed. As a result of study, it was determined that there was a significant relationship between the epistemological beliefs and metacognitive strategy use of ELT pre-service teachers in both formal and distance education programs.

Learning English in the Periphery: A View from Myanmar (Burma)

Science.gov (United States)

Tin, Tan Bee

2014-01-01

Although researchers have called for the investigation of local vernacular learning and teaching practices in various ELT (English language teaching) contexts, studies conducted in the Periphery are fewer in number. This study attempts to understand English learning experiences of a group of students from the Periphery, who were studying English…

Handwriting as a Tool for Learning in ELT

Science.gov (United States)

Lund, Ragnhild Elisabeth

2016-01-01

This article discusses the role that handwriting can have when writing is used as a tool for learning in English language education. Nineteen Norwegian EFL teacher training students were interviewed in focus groups about their own practices and their thoughts about writing-to-learn activities. All the students said that they prefer to write by…

European Extremely Large Telescope (E-ELT) availability stochastic model: integrating failure mode and effect analysis (FMEA), influence diagram, and Bayesian network together

Science.gov (United States)

Verzichelli, Gianluca

2016-08-01

An Availability Stochastic Model for the E-ELT has been developed in GeNIE. The latter is a Graphical User Interface (GUI) for the Structural Modeling, Inference, and Learning Engine (SMILE), originally distributed by the Decision Systems Laboratory from the University of Pittsburgh, and now being a product of Bayes Fusion, LLC. The E-ELT will be the largest optical/near-infrared telescope in the world. Its design comprises an Alt-Azimuth mount reflecting telescope with a 39-metre-diameter segmented primary mirror, a 4-metre-diameter secondary mirror, a 3.75-metre-diameter tertiary mirror, adaptive optics and multiple instruments. This paper highlights how a Model has been developed for an earlier on assessment of the Telescope Avail- ability. It also describes the modular structure and the underlying assumptions that have been adopted for developing the model and demonstrates the integration of FMEA, Influence Diagram and Bayesian Network elements. These have been considered for a better characterization of the Model inputs and outputs and for taking into account Degraded-based Reliability (DBR). Lastly, it provides an overview of how the information and knowledge captured in the model may be used for an earlier on definition of the Failure, Detection, Isolation and Recovery (FDIR) Control Strategy and the Telescope Minimum Master Equipment List (T-MMEL).

Characterization of exoplanet atmospheres using high-dispersion spectroscopy with the E-ELT and beyond

Directory of Open Access Journals (Sweden)

Snellen Ignas

2013-04-01

Full Text Available Ground-based high-dispersion (R ∼ 100,000 spectroscopy provides unique information on exoplanet atmospheres, inaccessible from space - even using the JWST or other future space telescopes. Recent successes in transmission- and dayside spectroscopy using CRIRES on the Very Large Telescope prelude the enormous discovery potential of high-dispersion spectrographs on the E-ELT, such as METIS in the thermal infrared, and HIRES in the optical/near-infrared. This includes the orbital inclination and masses of hundred(s of non-transiting planets, line-by-line molecular band spectra, planet rotation and global wind patterns, longitudinal spectral variations, and possibly isotopologue ratios. Thinking beyond the E-ELT, we advocate that ultimately a systematic search for oxygen in atmospheres of nearby Earth-like planets can be conducted using large arrays of relatively low-cost flux collector telescopes equipped with high-dispersion spectrographs.

ELT RESEARCH PAPERS AS AUTHENTIC MATERIALS IN TEACHING RESEARCH-BASED ARTICLE WRITING: A CASE IN INDONESIAN CONTEXT

Directory of Open Access Journals (Sweden)

M. Ali Ghufron

2017-09-01

Full Text Available There are strong shreds of evidence that the choice of instructional materials has large effects on students’ achievement. This study was to assess the efficacy of using ELT research papers as authentic materials in teaching research-based article writing. This study was aimed at revealing whether or not there is a significant difference in students’ writing skill in terms of ELT research paper writing between the students who were taught by using ELT research papers as authentic materials and those who were taught by using textbook materials provided by the faculty. This study belongs to a quasi-experimental study with an experimental and control group pretest-posttest design. The population of this study was 75 students from the fourth semester of English Education Study Program of IKIP PGRI Bojonegoro, East Java, Indonesia. The sample was selected through cluster random sampling and consisted of 50 students that were divided into two groups. The instrument used to collect the data was a writing test. Consequently, normality and homogeneity of the data were tested. A t-test was used to compare the mean of the two groups. The hypothesis was designed and tested at 0.05 level of significance. The results revealed that there is a significant difference in students’ academic writing skill between the students who were taught by using the ELT research papers as authentic materials and those who were taught by using textbook materials. The t-test revealed that t-value is higher than t-table (6.07>2.01. Therefore it is concluded that the authentic instructional materials could significantly improve students’ academic writing skill.

Design of pre-optics for laser guide star wavefront sensor for the ELT

Science.gov (United States)

Muslimov, Eduard; Dohlen, Kjetil; Neichel, Benoit; Hugot, Emmanuel

2017-12-01

In the present paper, we consider the optical design of a zoom system for the active refocusing in laser guide star wavefront sensors. The system is designed according to the specifications coming from the Extremely Large Telescope (ELT)-HARMONI instrument, the first-light, integral field spectrograph for the European (E)-ELT. The system must provide a refocusing of the laser guide as a function of telescope pointing and large decentring of the incoming beam. The system considers four moving lens groups, each of them being a doublet with one aspherical surface. The advantages and shortcomings of such a solution in terms of the component displacements and complexity of the surfaces are described in detail. It is shown that the system can provide the median value of the residual wavefront error of 13.8-94.3 nm and the maximum value <206 nm, while the exit pupil distortion is 0.26-0.36% for each of the telescope pointing directions.

First results of the wind evaluation breadboard for ELT primary mirror design

Science.gov (United States)

Reyes García-Talavera, Marcos; Viera, Teodora; Núñez, Miguel

2010-07-01

The Wind Evaluation Breadboard (WEB) is a primary mirror and telescope simulator formed by seven aluminium segments, including position sensors, electromechanical support systems and support structures. WEB has been developed to evaluate technologies for primary mirror wavefront control and to evaluate the performance of the control of wind buffeting disturbance on ELT segmented mirrors. For this purpose WEB electro-mechanical set-up simulates the real operational constrains applied to large segmented mirrors. This paper describes the WEB assembly, integration and verification, the instrument characterisation and close loop control design, including the dynamical characterization of the instrument and the control architecture. The performance of the new technologies developed for position sensing, acting and controlling is evaluated. The integration of the instrument in the observatory and the results of the first experiments are summarised, with different wind conditions, elevation and azimuth angles of incidence. Conclusions are extracted with respect the wind rejection performance and the control strategy for an ELT. WEB has been designed and developed by IAC, ESO, ALTRAN and JUPASA, with the integration of subsystems of FOGALE and TNO.

Uudised : Olari Elts peadirigendiks Riiga. Kitarriöö uudisteosega. Täna algab kirikufestival / Priit Kuusk

Index Scriptorium Estoniae

Kuusk, Priit, 1938-

2001-01-01

O. Elts allkirjastas 30. juulil lepingu, millega ta saab Läti RSO peadirigendiks. Duo Bagger-Varts esines festivalil "Klaaspärlimäng", esiettekandele tuli J. Räätsa teos "Fragment". IX rahvusvahelisest kirikumuusika festivalist

ULE design considerations for a 3m class light weighted mirror blank for E-ELT M5

Science.gov (United States)

Fox, Andrew; Hobbs, Tom; Edwards, Mary; Arnold, Matthew; Sawyer, Kent

2016-07-01

It is expected that the next generation of large ground based astronomical telescopes will need large fast-steering/tip-tilt mirrors made of ultra-lightweight construction. These fast-steering mirrors are used to continuously correct for atmospheric disturbances and telescope vibrations. An example of this is the European Extremely Large Telescope (E-ELT) M5 lightweight mirror, which is part of the Tip-Tilt/Field-Stabilization Unit. The baseline design for the E-ELT M5 mirror, as presented in the E-ELT Construction Proposal, is a closed-back ULE mirror with a lightweight core using square core cells. Corning Incorporated (Corning) has a long history of manufacturing lightweight mirror blanks using ULE in a closed-back construction, going back to the 1960's, and includes the Hubble Space Telescope primary mirror, Subaru Telescope secondary and tertiary mirrors, the Magellan I and II tertiary mirrors, and Kepler Space Telescope primary mirror, among many others. A parametric study of 1-meter class lightweight mirror designs showed that Corning's capability to seal a continuous back sheet to a light-weighted core structure provides superior mirror rigidity, in a near-zero thermal expansion material, relative to other existing technologies in this design space. Corning has investigated the parametric performance of several design characteristics for a 3-meter class lightweight mirror blank for the E-ELT M5. Finite Element Analysis was performed on several design scenarios to obtain weight, areal density, and first Eigen frequency. This paper presents an overview of Corning ULE and lightweight mirror manufacturing capabilities, the parametric performance of design characteristics for 1-meter class and 3-meter class lightweight mirrors, as well as the manufacturing advantages and disadvantages of those characteristics.

End-to-End Operations in the ELT Era

Science.gov (United States)

Hainaut, O. R.; Bierwirth, T.; Brillant, S.; Mieske, S.; Patat, F.; Rejkuba, M.; Romaniello, M.; Sterzik, M.

2018-03-01

The Data Flow System is the infrastructure on which Very Large Telescope (VLT) observations are performed at the Observatory, before and after the observations themselves take place. Since its original conception in the late 1990s, it has evolved to accommodate new observing modes and new instruments on La Silla and Paranal. Several updates and upgrades are needed to overcome its obsolescence and to integrate requirements from the new instruments from the community and, of course, from ESO's Extremely Large Telescope (ELT), which will be integrated into Paranal's operations. We describe the end-to-end operations and the resulting roadmap guiding their further development.

ELT Research in Turkey: A Content Analysis of Selected Features of Published Articles

Science.gov (United States)

Yagiz, Oktay; Aydin, Burcu; Akdemir, Ahmet Selçuk

2016-01-01

This study reviews a selected sample of 274 research articles on ELT, published between 2005 and 2015 in Turkish contexts. In the study, 15 journals in ULAKBIM database and articles from national and international journals accessed according to convenience sampling method were surveyed and relevant articles were obtained. A content analysis was…

Beyond the Didactic Classroom: Educational Models to Encourage Active Student Involvement in Learning

OpenAIRE

Shreeve, Michael W.

2008-01-01

In a chiropractic college that utilizes a hybrid curriculum model composed of adult-based learning strategies along with traditional lecture-based course delivery, a literature search for educational delivery methods that would integrate the affective domain and the cognitive domain of learning provided some insights into the use of problem-based learning (PBL), experiential learning theory (ELT), and the emerging use of appreciative inquiry (AI) to enhance the learning experience. The purpos...

SimCADO: an instrument data simulator package for MICADO at the E-ELT

NARCIS (Netherlands)

Leschinski, K.; Czoske, O.; Köhler, R.; Mach, M.; Zeilinger, W.; Verdoes Kleijn, G.; Alves, J.; Kausch, W.; Przybilla, N.

2016-01-01

MICADO will be the first-light wide-field imager for the European Extremely Large Telescope (E-ELT) and will provide diffraction limited imaging (7mas at 1.2mm) over a 53 arc-second field of view. In order to support various consortium activities we have developed a first version of SimCADO: an

Status of E-ELT M5 scale-one demonstrator

Science.gov (United States)

Barriga, Pablo; Sedghi, Babak; Dimmler, Martin; Kornweibel, Nick

2014-07-01

The fifth mirror of the European Extremely Large Telescope optical train is a field stabilization tip/tilt unit responsible for correcting the dynamical tip and tilt caused mainly by wind load on the telescope. A scale-one prototype including the inclined support, the fixed frame and a basic control system was designed and manufactured by NTE-SENER (Spain) and CSEM (Switzerland) as part of the prototyping and design activities. All interfaces to the mirror have been reproduced on a dummy structure reproducing the inertial characteristics of the optical element. The M5 unit is required to have sufficient bandwidth for tip/tilt reference commands coming from the wavefront control system. Such a bandwidth can be achieved using local active damping loop to damp the low frequency mechanical modes before closing a position loop. Prototyping on the M5 unit has been undertaken in order to demonstrate the E-ELT control system architecture, concepts and development standards and to further study active damping strategies. The control system consists of two nested loops: a local damping loop and a position loop. The development of this control system was undertaken following the E-ELT control system development standards in order to determine their applicability and performance and includes hardware selection, communication, synchronization, configuration, and data logging. In this paper we present the current status of the prototype M5 control system and the latest results on the active damping control strategy, in particular the promising results obtained with the method of positive position feedback.

Recovering the colour-dependent albedo of exoplanets with high-resolution spectroscopy: from ESPRESSO to the ELT.

Science.gov (United States)

Martins, J. H. C.; Figueira, P.; Santos, N. C.; Melo, C.; Garcia Muñoz, A.; Faria, J.; Pepe, F.; Lovis, C.

2018-05-01

The characterization of planetary atmospheres is a daunting task, pushing current observing facilities to their limits. The next generation of high-resolution spectrographs mounted on large telescopes - such as ESPRESSO@VLT and HIRES@ELT - will allow us to probe and characterize exoplanetary atmospheres in greater detail than possible to this point. We present a method that permits the recovery of the colour-dependent reflectivity of exoplanets from high-resolution spectroscopic observations. Determining the wavelength-dependent albedo will provide insight into the chemical properties and weather of the exoplanet atmospheres. For this work, we simulated ESPRESSO@VLT and HIRES@ELT high-resolution observations of known planetary systems with several albedo configurations. We demonstrate how the cross correlation technique applied to theses simulated observations can be used to successfully recover the geometric albedo of exoplanets over a range of wavelengths. In all cases, we were able to recover the wavelength dependent albedo of the simulated exoplanets and distinguish between several atmospheric models representing different atmospheric configurations. In brief, we demonstrate that the cross correlation technique allows for the recovery of exoplanetary albedo functions from optical observations with the next generation of high-resolution spectrographs that will be mounted on large telescopes with reasonable exposure times. Its recovery will permit the characterization of exoplanetary atmospheres in terms of composition and dynamics and consolidates the cross correlation technique as a powerful tool for exoplanet characterization.

Workshop “Science with the VLT in the ELT Era”

CERN Document Server

Astrophysics and Space Science Proceedings

2008-01-01

The Workshop ‘Science with the VLT in the ELT era’ was organised by ESO as a forum for the astronomical community to debate its expected future use of ESO’s Very Large Telescope ( and its VLTI interferometric mode) when other facilities such as ALMA, JWST and, hopefully, at least one extremely large 30-40m class telescope will be operating. VLT/I science highlights were presented, future science priorities argued, synergies between the VLT and the future facilities confirmed and specific new VLT/I instruments proposed.

A Quasi-Experimental Examination: Cognitive Sequencing of Instruction Using Experiential Learning Theory for STEM Concepts in Agricultural Education

Science.gov (United States)

Smith, Kasee L.; Rayfield, John

2017-01-01

Understanding methods for effectively instructing STEM education concepts is essential in the current climate of education (Freeman, Marginson, & Tyler 2014). Kolb's experiential learning theory (ELT) outlines four specific modes of learning, based on preferences for grasping and transforming information. This quasi-experimental study was…

77 FR 28668 - Technical Standard Order (TSO)-C91a, Emergency Locator Transmitters (ELTs)

Science.gov (United States)

2012-05-15

... Aviation Administration, 470 L'Enfant Plaza, Suite 4102, Washington, DC 20024. Telephone (202) 385-4652... ELTs can optionally include a GPS position which can potentially reduce the search area to within 100... a GPS locator instead of the 121.5 homing beacon. The FAA acknowledges the benefits of including GPS...

The Science Case for Multi-Object Spectroscopy on the European ELT

OpenAIRE

Evans, Chris; Puech, Mathieu; Afonso, Jose; Almaini, Omar; Amram, Philippe; Aussel, Hervé; Barbuy, Beatriz; Basden, Alistair; Bastian, Nate; Battaglia, Giuseppina; Biller, Beth; Bonifacio, Piercarlo; Bouché, Nicholas; Bunker, Andy; Caffau, Elisabetta

2015-01-01

This White Paper presents the scientific motivations for a multi-object spectrograph (MOS) on the European Extremely Large Telescope (E-ELT). The MOS case draws on all fields of contemporary astronomy, from extra-solar planets, to the study of the halo of the Milky Way and its satellites, and from resolved stellar populations in nearby galaxies out to observations of the earliest 'first-light' structures in the partially-reionised Universe. The material presented here results from thorough di...

Project overview of OPTIMOS-EVE: the fibre-fed multi-object spectrograph for the E-ELT

NARCIS (Netherlands)

Navarro, R.; Chemla, F.; Bonifacio, P.; Flores, H.; Guinouard, I.; Huet, J.-M.; Puech, M.; Royer, F.; Pragt, J.H.; Wulterkens, G.; Sawyer, E.C.; Caldwell, M.E.; Tosh, I.A.J.; Whalley, M.S.; Woodhouse, G.F.W.; Spanò, P.; Di Marcantonio, P.; Andersen, M.I.; Dalton, G.B.; Kaper, L.; Hammer, F.

2010-01-01

OPTIMOS-EVE (OPTical Infrared Multi Object Spectrograph - Extreme Visual Explorer) is the fibre fed multi object spectrograph proposed for the European Extremely Large Telescope (E-ELT), planned to be operational in 2018 at Cerro Armazones (Chile). It is designed to provide a spectral resolution of

Studies and Suggestions on English Vocabulary Teaching and Learning

Science.gov (United States)

Zheng, Shigao

2012-01-01

To improve vocabulary learning and teaching in ELT settings, two questionnaires are designed and directed to more than 100 students and teachers in one of China's key universities. The findings suggest that an enhanced awareness of cultural difference, metaphorical competence, and learners' autonomy in vocabulary acquisition will effectively…

PENERAPAN MODEL PEMBELAJARAN GROUP INVESTIGATION DAN LECTURING UNTUK MENINGKATKAN PEMAHAMAN MAHASISWA TERHADAP MATERI ENGLISH TEACHING AND LEARNING THEORIES (ELT

Directory of Open Access Journals (Sweden)

Eva Nikmatul Rabbiyanti

2016-06-01

Full Text Available Merging two Methods between lecturing and Group Investigation are expected not only to develop active participation of students in the lecturing process but also to develop the ability of creative thinking, collaboration and presenting themselves in public, but the writer keep maintaining the use of lecturing methods to give control to the  delivery of the key points of the materials. The research was conducted on students of D class of the 4th semester, TBI Programs of STAIN Pamekasan at 2013/2014 year, totaling 34 students. The method used was classroom action research by using two cycles, in each cycle consists of Planning, Implementation, and the reflection. The results of this study indicate that, the ability of students' understanding of the course material ELT tends to increase in each cycle, with the average value of pre-cycle test was 45.29, and in the first cycle was 73.09, while in the second cycle was 79.00. with the percentage of completeness in cycle 1 was 85.29% while in the second cycle was 88.23%. Besides, the collaboration of this two models were also able to improve students analytical skills, the ability to express ideas and opinions in English, and also the ability to work together and present themselves in public. Based on the results of the study finally concluded, successful mechanism developed in this study consists of eleven stages, namely 1 the preparation phase, 2 the learning objective delivery, 3 aperseption delivery, 4 the new material delivery, 5 brain storming, 6 topics identification and grouping, 7 distribution of job decriptions, 8 conducting the investigation, 9 preparation of the final report, 10 Present the final report, 11 Evaluation of the achievement

Moodle: A Way for Blending VLE and Face-to-Face Instruction in the ELT Context?

Science.gov (United States)

Ilin, Gulden

2013-01-01

This classroom research explores the probable consequences of a blended Teaching English to Young Learners (TEYLs) course comprised of Moodle applications and face to face instruction in the English Language Teaching (ELT) context. Contrary to previous face to face only procedure, the course was divided into two segments: traditional classroom…

“That’s the biggest impact!” Pedagogical values of movies in ELT classrooms

Directory of Open Access Journals (Sweden)

Nyak Mutia Ismail

2017-09-01

Full Text Available Since many say watching movies can have a positive effect on language learning outcomes, this research was done to find out which skills movies can contribute most to, whether speaking, listening, reading, writing, vocabulary, grammar or cultural aspects. A qualitative research method was used for this study. This study was done to find out the teachers’ perceptions of using English movies in English Language Teaching (ELT processes. Teachers from three different levels: primary, secondary, and senior high-school teachers were asked to answer a questionnaire set in accordance with the research topic. Five of them were senior high school teachers, two of them were junior high school teachers, and three of them were elementary school teachers. Creative interviews were also used as an additional data source. The results showed that most of the teachers agreed that movies play their biggest role and considerable advantages in developing cultural aspects and listening skills. Furthermore, some integration is possible between listening and speaking as well as with reading and writing because watching movies works better with integration of skills. Apparently, even though vocabulary can develop with this technique, grammar is not enhanced alone without being accompanied by writing.

Exploring ELT Students' Awareness of the Differences between the British and American Varieties of English

Science.gov (United States)

Yaman, Ismail

2015-01-01

This study aims to find out the extent to which students attending the English Language Teaching Programme (ELT) at Ondokuz Mayis University are aware of the major spelling, vocabulary, and pronunciation differences between American and British English which constitute the most commonly used varieties of English. To this end, 42 randomly selected…

The E-ELT project: the telescope main structure detailed design study

Science.gov (United States)

Marchiori, Gianpietro; Busatta, Andrea; Ghedin, Leonardo; De Lorenzi, Simone

2012-09-01

The European Extremely Large Telescope (E-ELT) is the biggest telescope in the world. Within the Detailed Design activities, ESO has awarded EIE GROUP (European Industrial Engineering) a contract for the Design of the Main Structure to the point where the concept of the telescope has been consolidated, from a construction point of view. All the Design activities have been developed in order to create an integrated system in terms of functionality and performance, while the engineering activities have been performed with the aim of obtaining a telescope that can be built, transported, integrated, with a reduced maintainability.

A new test facility for the E-ELT infrared detector program

Science.gov (United States)

Lizon, Jean Louis; Amico, Paola; Brinkmann, Martin; Delabre, Bernard; Finger, Gert; Guidolin, Ivan Maria; Guzman, Ronald; Hinterschuster, Renate; Ives, Derek; Klein, Barbara; Quattri, Marco

2016-08-01

During the development of the VLT instrumentation program, ESO acquired considerable expertise in the area of infrared detectors, their testing and optimizing their performance. This can mainly be attributed to a very competent team and most importantly to the availability of a very well suited test facility, namely, IRATEC. This test facility was designed more than 15 years ago, specifically for 1K × 1K detectors such as the Aladdin device, with a maximum field of only 30 mm square. Unfortunately, this facility is no longer suited for the testing of the new larger format detectors that are going to be used to equip the future E-ELT instruments. It is projected that over the next 20 years, there will be of the order of 50-100 very large format detectors to be procured and tested for use with E-ELT first and second generation instruments and VLT third generation instruments. For this reason ESO has initiated the in-house design and construction of a dedicated new IR detector arrays test facility: the Facility for Infrared Array Testing (FIAT). It will be possible to mount up to four 60 mm square detectors in the facility, as well as mosaics of smaller detectors. It is being designed to have a very low thermal background such that detectors with 5.3 μm cut-off material can routinely be tested. The paper introduces the most important use cases for which FIAT is designed: they range from performing routine performance measurements on acquired devices, optimization setups for custom applications (like spot scan intra-pixel response, persistence and surface reflectivity measurements), test of new complex operation modes (e.g. high speed subwindowing mode for low order sensing, flexure control, etc.) and the development of new tests and calibration procedures to support the scientific requirements of the E-ELT and to allow troubleshooting the unexpected challenges that arise when a new detector system is brought online. The facility is also being designed to minimize

Kaks rauast nooleotsa Jägala Jõesuu linnamäelt: arheoloogiline ja ajalooline kontekst / Mari Lõhmus, Ester Oras, Martti Veldi

Index Scriptorium Estoniae

Lõhmus, Mari

2010-01-01

Jägala Jõesuu linnamäelt leitud vanemast rauaajast pärit kahest nooleotsast. Nooleotste avastamisest ja konserveerimisest ning olemasoleva info põhjal tehtud vaadetest minevikku. Nooleotsad viitavad rauaajal toimunud sõjalisele konfliktile Läänemere piirkonnas

ELT Teacher Education Flipped Classroom: An Analysis of Task Challenge and Student Teachers' Views and Expectations

Science.gov (United States)

Karaaslan, Hatice; Çelebi, Hatice

2017-01-01

In this study, we explore the interplay between task complexity, task conditions and task difficulty introduced by Robinson (2001) in flipped classroom instruction at tertiary level through the data we collected from undergraduate English Language Teaching (ELT) department students studying at an English-medium state university. For the…

Learning Time and Educational Effectiveness.

Science.gov (United States)

Anderson, Lorin W.

1980-01-01

To explore the relationship between time and school learning, this paper defines the three kinds of learning time identified by researchers--allocated time, time-on-task, and academic learning time--and relates them to curriculum development. The author cites evidence that time-on-task is related to student achievement and describes two…

Extrasolar Planets Observed with JWST and the ELTs

Science.gov (United States)

Deming, L. Drake

2010-01-01

The advent of cryogenic space-borne infrared observatories such as the Spitzer Space Telescope has lead to a revolution in the study of planets and planetary systems orbiting sun-like stars. Already Spitzer has characterized the emergent infrared spectra of close-in giant exoplanets using transit and eclipse techniques. The James Webb Space Telescope (JWST) will be able to extend these studies to superEarth exoplanets orbiting in the habitable zones of M-dwarf stars in the near solar neighborhood. The forthcoming ground-based Extremely Large Telescopes (ELTs) will playa key role in these studies, being especially valuable for spectroscopy at higher spectral resolving powers where large photon fluxes are needed. The culmination of this work within the next two decades will be the detection and spectral characterization of the major molecular constituents in the atmosphere of a habitable superEarth orbiting a nearby lower main sequence star.

ELT Teacher Trainees' Self-Perceptions and Awareness of the Pronunciation Skill, and Their Attitudes towards Its Instruction

Science.gov (United States)

Gürsoy, Esim; Hüseyinoglu, Madina

2017-01-01

Having received the stamp of an "often neglected" element in second language teaching, opinions of English Language Teaching (ELT) Teacher Trainees (TT) taking pronunciation as an explicit instruction course seem to be neglected in research advocated in this field as well. Moreover, features of pronunciation (segmentals and…

Where the Difference Lies: Teachers' Perceptions toward Cultural Content of ELT Books in Three Circles of World Englishes

Science.gov (United States)

Monfared, Abbas; Mozaheb, Mohammad Amin; Shahiditabar, Mostafa

2016-01-01

Drawing on the literature on culture and intercultural communication, current discussions surrounding English as an international language (EIL), and cultural appropriation of ELT books in local communities, this article reports the findings of a qualitative and qualitative research study with English language teachers from Inner (40 American, 36…

E-ELT M5 field stabilisation unit scale 1 demonstrator design and performances evaluation

Science.gov (United States)

Casalta, J. M.; Barriga, J.; Ariño, J.; Mercader, J.; San Andrés, M.; Serra, J.; Kjelberg, I.; Hubin, N.; Jochum, L.; Vernet, E.; Dimmler, M.; Müller, M.

2010-07-01

The M5 Field stabilization Unit (M5FU) for European Extremely Large Telescope (E-ELT) is a fast correcting optical system that shall provide tip-tilt corrections for the telescope dynamic pointing errors and the effect of atmospheric tiptilt and wind disturbances. A M5FU scale 1 demonstrator (M5FU1D) is being built to assess the feasibility of the key elements (actuators, sensors, mirror, mirror interfaces) and the real-time control algorithm. The strict constraints (e.g. tip-tilt control frequency range 100Hz, 3m ellipse mirror size, mirror first Eigen frequency 300Hz, maximum tip/tilt range +/- 30 arcsec, maximum tiptilt error < 40 marcsec) have been a big challenge for developing the M5FU Conceptual Design and its scale 1 demonstrator. The paper summarises the proposed design for the final unit and demonstrator and the measured performances compared to the applicable specifications.

Prefocal station mechanical design concept study for the E-ELT

Science.gov (United States)

Jolley, Paul; Brunetto, Enzo; Frank, Christoph; Lewis, Steffan; Marchetti, Enrico

2016-07-01

The Nasmyth platforms of the E-ELT will contain one Prefocal Station (PFS) each. The main PFS functional requirements are to provide a focal plane to the three Nasmyth focal stations and the Coudé focus, optical sensing supporting telescope low order optimisation and seeing limited image quality, and optical sensing supporting characterising and phasing of M1 and other telescope subsystems. The PFS user requirements are used to derive the PFS technical requirements specification that will form the basis for design, development and production of the system. This specification process includes high-level architectural decisions and technical performance budget allocations. The mechanical design concepts reported here have been developed in order to validate key system specifications and associated technical budgets.

Assessing ELT Pre-Service Teachers via Web 2.0 Tools: Perceptions toward Traditional, Online and Alternative Assessment

Science.gov (United States)

Cirit, Nazli Ceren

2015-01-01

The purpose of this study is to investigate the perceptions of the ELT pre-service teachers toward the traditional, alternative, and online assessment methods and examine whether the participants' attitudes change toward the types of assessment after the tasks via Web 2.0 tools are implemented. In the light of these aims, the study was conducted…

The Implications of Expanding the Instruction Time for the English Language Teaching Policy Implementation in the Sultanate of Oman: A Qualitative Study

Science.gov (United States)

Al-Issa, Ali S. M.

2013-01-01

This study asks questions and elicits answers about the importance of English language teaching (ELT) instruction time on the national curriculum in the Sultanate of Oman from an ideological perspective. It triangulates data from semi-structured interviews made with different agents involved in the Omani ELT system and representing different…

Students’ Learning Styles: An Ethnographic Case Study at UIN Walisongo Semarang

Directory of Open Access Journals (Sweden)

Muhammad Nafi Annury

2016-07-01

Full Text Available This research is aimed to know what kinds of learning preferences are students intended most? And how many types of learners’ characteristics appear in ELT classrooms? This research was conducted through qualitative approach. This means that the data are collected not in the form of numbers, the data are taken from questionnaires, documentation, and observation. The results of this study are as follows: students of ELT program at UIN Walisongo Semarang tend to study by various kind of learning. It can be proved that First, regarding to the description of 2A class which has 11.2% visual students, 16.02% of audio-lingual, 5% kinaesthetic and 14.11% are others, would use multimedia which is available in the classroom. Whereas, the description of 2B class has shown that 13% students are visual learners, 11% audio-lingual learners, 6.72% kinaesthetic and 13,72% are others. Last but not least, there are 12% visual learners, 11.17% audio-lingual, 7.25 kinaesthetic and the rest 14% others. Furthermore, there are four characteristics which appear from the research, they are as follows: visual learners, auditory learners, kinaesthetic learners, and other characteristics.

STUDENTS’ LEARNING STYLES: AN ETHNOGRAPHIC CASE STUDY AT UIN WALISONGO SEMARANG

Directory of Open Access Journals (Sweden)

Muhammad Nafi Annury

2016-07-01

Full Text Available This research is aimed to know what kinds of learning preferences are students intended most? And how many types of learners’ characteristics appear in ELT classrooms? This research was conducted through qualitative approach. This means that the data are collected not in the form of numbers, the data are taken from questionnaires, documentation, and observation. The results of this study are as follows: students of ELT program at UIN Walisongo Semarang tend to study by various kind of learning. It can be proved that First, regarding to the description of 2A class which has 11.2% visual students, 16.02% of audio-lingual, 5% kinaesthetic and 14.11% are others, would use multimedia which is available in the classroom. Whereas, the description of 2B class has shown that 13% students are visual learners, 11% audio-lingual learners, 6.72% kinaesthetic and 13,72% are others. Last but not least, there are 12% visual learners, 11.17% audio-lingual, 7.25 kinaesthetic and the rest 14% others. Furthermore, there are four characteristics which appear from the research, they are as follows: visual learners, auditory learners, kinaesthetic learners, and other characteristics.

The Role of Electronic Learning Technology in Networks Systems

International Nuclear Information System (INIS)

Abd ELhamid, A.; Ayad, N.M.A.; Fouad, Y.; Abdelkader, T.

2016-01-01

Recently, Electronic Learning Technology (ELT) has been widely spread as one of the new technologies in the world through using Information and Communication Technology (ICT). One of the strategies of ELT is Simulation, for instance Military and Medical simulations that are used to avoid risks and reduce Costs. A wireless communication network refers to any network not physically connected by cables, which enables the desired convenience and mobility for the user. Wireless communication networks have been useful in areas such as commerce, education and defense. According to the nature of a particular application, they can be used in home-based and industrial systems or in commercial and military environments. Historically, Mobile Ad-hoc Networks (MANET) have primarily been used for tactical military network related applications to improve battlefield communications/ survivability. MANET is a collection of wireless nodes that can dynamically be set up anywhere and anytime without using any pre-existing network infrastructure. Mobility in wireless networks basically refers to nodes changing its point of attachment to the network. Also, how the end terminals can move, there are many mobility models described the movement of nodes, many researchers use the Random Way point Mobility Model (RWPM). In this paper, a Graphical User Interface (GUI) for RWPM simulation is introduced as a proposal to be used through ELT Project. In the research area of computer and communications networks, simulation is a very useful technique for the behavior of networks

Uudised : EMA uus barokkorel. Olari Elts Soome Raadio SO ees. "Supreme Silence" Saksamaal. Kangro muusika Lätis ja Leedus / Priit Kuusk

Index Scriptorium Estoniae

Kuusk, Priit, 1938-

2001-01-01

EMA vastvalminud barokkoreli avamispidustustest. O.Elts juhatas 30. apr. Finlandia-talos toimunud kontserdil Soome Raadio SO-d. P.Vähi teos "Supreme Silence" kõlas kahel muusikafestivalil Saksamaal. Läti klaveriduo esitas rahvusvahelisel klaveriduode festivalil Lätis ja Leedus R.Kangro pala "O Sancta Simplicitas!"

An Investigation Into the Culture and Social Actors Representation in Summit Series ELT Textbooks Within van Leeuwen’s 1996 Framework

Directory of Open Access Journals (Sweden)

Nasser Rashidi

2015-03-01

Full Text Available The current study aims at identifying particular ways through which social actors are represented in Summit Series ELT textbooks. It examines cultural load in the textbooks within critical discourse analysis framework, in this case van Leeuwen’s framework. Particularly, the study attempts to explore if values, norms, and roles are culture/context-bound. Results of the analyses showed that among discursive features, Inclusion, Genericization, and Indetermination were used more than Exclusion, Specification, and Determination. Activation was more observed than Passivation, and Categorization had an important function in the representation of some of the social actors along with Assimilation and Impersonalization. The analysis also indicated the impartiality toward the representation of social actors. Moral, social, and personal values were the most disseminated values, while social morality and traditions had the highest occurrence. However, a few discriminative cases were found regarding gender roles. The researchers proposed that Summit Series were less grounded in cultural assumptions/biases. This impartiality eases language learning by keeping learners away from misunderstanding and incomprehensibility.

Establishing Time for Professional Learning

Science.gov (United States)

Journal of Staff Development, 2013

2013-01-01

Time for collaborative learning is an essential resource for educators working to implement college- and career-ready standards. The pages in this article include tools from the workbook "Establishing Time for Professional Learning." The tools support a complete process to help educators effectively find and use time. The following…

ELT Materials: The Key to Fostering Effective Teaching and Learning Settings

Directory of Open Access Journals (Sweden)

Astrid Núñez Pardo

2009-10-01

Full Text Available Our article aims at providing teachers with an overview for materials development, taking into account the experience gained by two teachers in the English Programme of the School of Education at Universidad Externado de Colombia in Bogotá. This experience has helped us achieve better teaching and learning conditions for our university students in their quest to learn a foreign language. This paper addresses the issue of the role of teachers as textbook developers, and how they can meet materials development demands by integrating a clear conceptualisation and set of principles as well as their essential components.

A mechanical design concept for EAGLE on the revised E-ELT

Science.gov (United States)

Dubbeldam, Cornelis M.

2014-07-01

ESO have recently revisited the design of the E-ELT with a view to reducing cost, leading to de-scopes which include a smaller primary aperture and removal of the Gravity Invariant Focal Station (GIFS). In its original concept, the EAGLE instrument was designed to be located at the GIFS and consequently a major mechanical re-design was required to enable the instrument to be placed on its side in a conventional straight-through Nasmyth configuration. In this paper, a conceptual design for a new instrument structure is presented. A preliminary finite element analysis was carried out to assess the structure's behaviour under operating loading conditions (e.g. gravity loads). The results of this analysis demonstrate that the proposed design is viable, without any significant degradation in performance compared to the original GIFS design.

Quality of E-Learners’ Time and Learning Performance Beyond Quantitative Time-on-Task

Directory of Open Access Journals (Sweden)

Margarida Romero

2011-06-01

Full Text Available AbstractAlong with the amount of time spent learning (or time-on-task, the quality of learning time has a real influence on learning performance. Quality of time in online learning depends on students’ time availability and their willingness to devote quality cognitive time to learning activities. However, the quantity and quality of the time spent by adult e-learners on learning activities can be reduced by professional, family, and social commitments. Considering that the main time pattern followed by most adult e-learners is a professional one, it may be beneficial for online education programs to offer a certain degree of flexibility in instructional time that might allow adult learners to adjust their learning times to their professional constraints. However, using the time left over once professional and family requirements have been fulfilled could lead to a reduction in quality time for learning. This paper starts by introducing the concept of quality of learning time from an online student-centred perspective. The impact of students’ time-related variables (working hours, time-on-task engagement, time flexibility, time of day, day of week is then analyzed according to individual and collaborative grades achieved during an online master’s degree program. The data show that both students’ time flexibility (r = .98 and especially their availability to learn in the morning are related to better grades in individual (r = .93 and collaborative activities (r = .46.

Timepiece: Extending and Enhancing Learning Time.

Science.gov (United States)

Anderson, Lorin W., Ed.; Walberg, Herbert J., Ed.

This publication offers suggestions for making more productive use of time, a scarce and valued educational resource. The chapter authors, authorities on the use of educational time, write about how to extend and enhance learning time within and outside schools. In "Productive Use of Time," Herbert Walberg describes how learning time can be…

ERASMUS-F: pathfinder for an E-ELT 3D instrumentation

Science.gov (United States)

Kelz, Andreas; Roth, Martin M.; Bacon, Roland; Bland-Hawthorn, Joss; Nicklas, Harald E.; Bryant, Julia J.; Colless, Matthew; Croom, Scott; Ellis, Simon; Fleischmann, Andreas; Gillingham, Peter; Haynes, Roger; Hopkins, Andrew; Kosmalski, Johan; O'Byrne, John W.; Olaya, Jean-Christophe; Rambold, William N.; Robertson, Gordon

2010-07-01

ERASMUS-F is a pathfinder study for a possible E-ELT 3D-instrumentation, funded by the German Ministry for Education and Research (BMBF). The study investigates the feasibility to combine a broadband optical spectrograph with a new generation of multi-object deployable fibre bundles. The baseline approach is to modify the spectrograph of the Multi-Unit Spectroscopic Explorer (MUSE), which is a VLT integral-field instrument using slicers, with a fibre-fed input. Taking advantage of recent developments in astrophotonics, it is planed to equip such an instrument with fused fibre bundles (hexabundles) that offer larger filling factors than dense-packed classical fibres. The overall project involves an optical and mechanical design study, the specifications of a software package for 3Dspectrophotometry, based upon the experiences with the P3d Data Reduction Software and an investigation of the science case for such an instrument. As a proof-of-concept, the study also involves a pathfinder instrument for the VLT, called the FIREBALL project.

Time factor in e-learning and assessment

OpenAIRE

Romero Velasco, Margarida

2010-01-01

Peer-reviewed Peer reviewed Time is probably one of the most polysemous words in education. In e-learning, characterization of the time factor is particularly relevant because of the high level of flexibility in the teaching and learning times, and the resulting responsibility of the e-learners in regulating their learning times.

Hard Times for HRD, Lean Times for Learning?: Workplace Participatory Practices as Enablers of Learning

Science.gov (United States)

Warhurst, Russell

2013-01-01

Purpose: This article aims to show how in times of austerity when formal HRD activity is curtailed and yet the need for learning is greatest, non-formal learning methods such as workplace involvement and participation initiated by line managers can compensate by enabling the required learning and change. Design/methodology/approach: A qualitative…

Profiling academic research on discourse studies and second language learning

Directory of Open Access Journals (Sweden)

Harold Castañeda

2012-06-01

Full Text Available There is little profiling academic research on discourse studies in relation to second language learning from a regional perspective. Thisstudy aims at unveiling what, when, where and who constitute scholarly work in research about these two interrelated fields. A dataset wasconfigured from registers taken from Dialnet and studied using specialized text-mining software. Findings revealed myriad research interests,few prolific years and the lack of networking. It is recommended to trace out our research as an ELT community locally and globally.

Elevated temperature intensity, timing, and duration of exposure affect soybean internode elongation, mainstem node number, and pod number per plant

Directory of Open Access Journals (Sweden)

Leon Hartwell Allen, Jr.

2018-04-01

Full Text Available A study was conducted in four compartments of a polycarbonate greenhouse at Gainesville, FL, USA to investigate how a soybean (Glycine max L. Merr. cultivar, Maverick (maturity group III, indeterminate, responded to three elevated temperatures, ELT, (day/night of 34/26 °C, 38/30 °C, and 42/34 °C in comparison to a control growth temperature (30/22 °C. Carbon dioxide (CO2 concentration was maintained at 700 μmol mol−1 in each compartment by a processor controlled air-sampling and CO2-injection system. Three sequential experiments were conducted at different times of year (summer, autumn, and early spring to investigate the effect of intensity, timing, and duration of ELT on soybean node number, internode elongation, mainstem length, and number of pods set per plant. At the control temperature, the soybean plants grown in the polycarbonate greenhouse were taller than field-grown plants. When plants were grown under continuous ELT applied soon after sowing or at initial flowering, the number of nodes increased with increasing ELT intensity, whereas the length of individual internodes decreased. When ELT treatment was applied during the beginning of flowering stage (R1–R2 or earlier, more nodes were produced and the length of affected internodes was decreased. When the ELT was imposed later at reproductive stage R5+ just before the beginning of seed filling, effects on node numbers and internode lengths were negligible. Short-term (10-day duration of ELT applied at four stages from V3 to R5+ did not significantly affect final mean numbers of nodes or mean mainstem lengths. Possible mechanisms of elevated temperature effects on soybean internode elongation and node number (internode number are discussed. Total pod numbers per plant increased linearly with mainstem node numbers and mainstem length. Furthermore, total pod numbers per plant were greatest at 34/26 °C rather than at the control temperature of 30/22 °C (and

Refined adaptive optics simulation with wide field of view for the E-ELT

International Nuclear Information System (INIS)

Chebbo, Manal

2012-01-01

Refined simulation tools for wide field AO systems (such as MOAO, MCAO or LTAO) on ELTs present new challenges. Increasing the number of degrees of freedom (scales as the square of the telescope diameter) makes the standard simulation's codes useless due to the huge number of operations to be performed at each step of the Adaptive Optics (AO) loop process. This computational burden requires new approaches in the computation of the DM voltages from WFS data. The classical matrix inversion and the matrix vector multiplication have to be replaced by a cleverer iterative resolution of the Least Square or Minimum Mean Square Error criterion (based on sparse matrices approaches). Moreover, for this new generation of AO systems, concepts themselves will become more complex: data fusion coming from multiple Laser and Natural Guide Stars (LGS / NGS) will have to be optimized, mirrors covering all the field of view associated to dedicated mirrors inside the scientific instrument itself will have to be coupled using split or integrated tomography schemes, differential pupil or/and field rotations will have to be considered, etc. All these new entries should be carefully simulated, analysed and quantified in terms of performance before any implementation in AO systems. For those reasons I developed, in collaboration with the ONERA, a full simulation code, based on iterative solution of linear systems with many parameters (use of sparse matrices). On this basis, I introduced new concepts of filtering and data fusion (LGS / NGS) to effectively manage modes such as tip, tilt and defocus in the entire process of tomographic reconstruction. The code will also eventually help to develop and test complex control laws (Multi-DM and multi-field) who have to manage a combination of adaptive telescope and post-focal instrument including dedicated deformable mirrors. The first application of this simulation tool has been studied in the framework of the EAGLE multi-object spectrograph

Radiologists' preferences for just-in-time learning.

Science.gov (United States)

Kahn, Charles E; Ehlers, Kevin C; Wood, Beverly P

2006-09-01

Effective learning can occur at the point of care, when opportunities arise to acquire information and apply it to a clinical problem. To assess interest in point-of-care learning, we conducted a survey to explore radiologists' attitudes and preferences regarding the use of just-in-time learning (JITL) in radiology. Following Institutional Review Board approval, we invited 104 current radiology residents and 86 radiologists in practice to participate in a 12-item Internet-based survey to assess their attitudes toward just-in-time learning. Voluntary participation in the survey was solicited by e-mail; respondents completed the survey on a web-based form. Seventy-nine physicians completed the questionnaire, including 47 radiology residents and 32 radiologists in practice; the overall response rate was 42%. Respondents generally expressed a strong interest for JITL: 96% indicated a willingness to try such a system, and 38% indicated that they definitely would use a JITL system. They expressed a preference for learning interventions of 5-10 min in length. Current and recent radiology trainees have expressed a strong interest in just-in-time learning. The information from this survey should be useful in pursuing the design of learning interventions and systems for delivering just-in-time learning to radiologists.

Learning During Stressful Times

Science.gov (United States)

Shors, Tracey J.

2012-01-01

Stressful life events can have profound effects on our cognitive and motor abilities, from those that could be construed as adaptive to those not so. In this review, I discuss the general notion that acute stressful experience necessarily impairs our abilities to learn and remember. The effects of stress on operant conditioning, that is, learned helplessness, as well as those on classical conditioning procedures are discussed in the context of performance and adaptation. Studies indicating sex differences in learning during stressful times are discussed, as are those attributing different responses to the existence of multiple memory systems and nonlinear relationships. The intent of this review is to highlight the apparent plasticity of the stress response, how it might have evolved to affect both performance and learning processes, and the potential problems with interpreting stress effects on learning as either good or bad. An appreciation for its plasticity may provide new avenues for investigating its underlying neuronal mechanisms. PMID:15054128

An algorithm for learning real-time automata

NARCIS (Netherlands)

Verwer, S.E.; De Weerdt, M.M.; Witteveen, C.

2007-01-01

We describe an algorithm for learning simple timed automata, known as real-time automata. The transitions of real-time automata can have a temporal constraint on the time of occurrence of the current symbol relative to the previous symbol. The learning algorithm is similar to the redblue fringe

Discovery of a Potent Class of PI3Kα Inhibitors with Unique Binding Mode via Encoded Library Technology (ELT).

Science.gov (United States)

Yang, Hongfang; Medeiros, Patricia F; Raha, Kaushik; Elkins, Patricia; Lind, Kenneth E; Lehr, Ruth; Adams, Nicholas D; Burgess, Joelle L; Schmidt, Stanley J; Knight, Steven D; Auger, Kurt R; Schaber, Michael D; Franklin, G Joseph; Ding, Yun; DeLorey, Jennifer L; Centrella, Paolo A; Mataruse, Sibongile; Skinner, Steven R; Clark, Matthew A; Cuozzo, John W; Evindar, Ghotas

2015-05-14

In the search of PI3K p110α wild type and H1047R mutant selective small molecule leads, an encoded library technology (ELT) campaign against the desired target proteins was performed which led to the discovery of a selective chemotype for PI3K isoforms from a three-cycle DNA encoded library. An X-ray crystal structure of a representative inhibitor from this chemotype demonstrated a unique binding mode in the p110α protein.

E-Learning, Time and Unconscious Thinking

Science.gov (United States)

Mathew, David

2014-01-01

This article views the temporal dimensions of e-learning through a psychoanalytic lens, and asks the reader to consider links between online learning and psychoanalysis. It argues that time and its associated philosophical puzzles impinge on both psychoanalytic theory and on e-learning at two specific points. The first is in the distinction…

Evaluation of software and electronics technologies for the control of the E-ELT instruments: a case study

International Nuclear Information System (INIS)

Di Marcantonio, P.; Cirami, R.; Coretti, I.; Chiozzi, G.; Kiekebusch, M.

2012-01-01

In the scope of the evaluation of architecture and technologies for the control system of the E-ELT (European-Extremely Large Telescope) instruments, a collaboration has been set up between the Instrumentation and Control Group of the INAF-OATs and the ESO Directorate of Engineering. The first result of this collaboration is the design and implementation of a prototype of a small but representative control system for a kind of multi-object (optical) spectrograph. The electronics has been based on PLCs (Programmable Logical Controller) and Ethernet based field-buses from different vendors but using international standards like the IEC 61131-3 and PLCopen Motion Control. The baseline design for the control software follows the architecture of the VLT (Very Large Telescope) Instrumentation application framework but it has been implemented using the ACS (ALMA Common Software), an open source software framework developed for the ALMA project and based on CORBA middle-ware. The communication among the software components is based on two models: CORBA calls for command/reply using the client/server paradigm and CORBA notification channel for distributing the devices status using the publisher/subscriber paradigm. The communication with the PLCs is based on OPC UA, an international standard for the communication with industrial controllers. The results of this work will contribute to the definition of the architecture of the control system that will be provided to all consortia responsible for the actual implementation of the E-ELT instruments. This paper presents the prototype motivation, its architecture, design and implementation. (authors)

The native-speaker fever in English language teaching (ELT: Pitting pedagogical competence against historical origin

Directory of Open Access Journals (Sweden)

Anchimbe, Eric A.

2006-01-01

Full Text Available This paper discusses English language teaching (ELT around the world, and argues that as a profession, it should emphasise pedagogical competence rather than native-speaker requirement in the recruitment of teachers in English as a foreign language (EFL and English as a second language (ESL contexts. It establishes that being a native speaker does not make one automatically a competent speaker or, of that matter, a competent teacher of the language. It observes that on many grounds, including physical, sociocultural, technological and economic changes in the world as well as the status of English as official and national language in many post-colonial regions, the distinction between native and non-native speakers is no longer valid.

Race and ethnicity in English language teaching Korea in focus

CERN Document Server

Jenks, Christopher Joseph

2017-01-01

This book examines racism and racialized discourses in the ELT profession in South Korea. The book argues that language teaching and learning is shaped by White normativity, an ideological commitment and a form of racialized discourse that comes from the social actions of those involved in the ELT profession.

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

Time will tell: The role of mobile learning analytics in self-regulated learning

NARCIS (Netherlands)

Tabuenca, Bernardo; Kalz, Marco; Drachsler, Hendrik; Specht, Marcus

2015-01-01

This longitudinal study explores the effects of tracking and monitoring time devoted to learn with a mobile tool, on self-regulated learning. Graduate students (n = 36) from three different online courses used their own mobile devices to track how much time they devoted to learn over a period of

ACTIVE LEARNING STRATEGIES IN TEACHING CROSS CULTURAL UNDERSTANDING FOR ENGLISH EDUCATION STUDENTS

Directory of Open Access Journals (Sweden)

Ikke Dewi Pratama

2017-02-01

Full Text Available Cross Cultural Understanding (CCU is one of required courses in English Language Teaching which aims at connecting language and culture so that language learners can use foreign language appropriately, i.e. appropriate forms of language for appropriate context of situation. However, some obstacles usually occur during the course, for examples: students’ lack of understanding that lead to opinions stating that this is a boring and useless course, and large number of students within a class where lecturer must teach more than 40 students in one class. Considering the importance of CCU course as well as the needs to overcome the problems during this course, this paper proposes some particular teaching strategies to help students in apprehending CCU materials through students’ active participations. Active learning strategies are preferred by means of raising students’ participation and critical thinking so that the class would run more effectively. Other consideration in composing the strategies is to prepare English Education students to be future English language teachers by training their ability in teaching performance as well as connecting language and culture in English Language Teaching (ELT.   Keywords: language, culture, strategies, media, ELT

Discovery of Potent and Selective Inhibitors for ADAMTS-4 through DNA-Encoded Library Technology (ELT).

Science.gov (United States)

Ding, Yun; O'Keefe, Heather; DeLorey, Jennifer L; Israel, David I; Messer, Jeffrey A; Chiu, Cynthia H; Skinner, Steven R; Matico, Rosalie E; Murray-Thompson, Monique F; Li, Fan; Clark, Matthew A; Cuozzo, John W; Arico-Muendel, Christopher; Morgan, Barry A

2015-08-13

The aggrecan degrading metalloprotease ADAMTS-4 has been identified as a novel therapeutic target for osteoarthritis. Here, we use DNA-encoded Library Technology (ELT) to identify novel ADAMTS-4 inhibitors from a DNA-encoded triazine library by affinity selection. Structure-activity relationship studies based on the selection information led to the identification of potent and highly selective inhibitors. For example, 4-(((4-(6,7-dimethoxy-3,4-dihydroisoquinolin-2(1H)-yl)-6-(((4-methylpiperazin-1-yl)methyl)amino)-1,3,5-triazin-2-yl)amino)methyl)-N-ethyl-N-(m-tolyl)benzamide has IC50 of 10 nM against ADAMTS-4, with >1000-fold selectivity over ADAMT-5, MMP-13, TACE, and ADAMTS-13. These inhibitors have no obvious zinc ligand functionality.

C. elegans GATA factors EGL-18 and ELT-6 function downstream of Wnt signaling to maintain the progenitor fate during larval asymmetric divisions of the seam cells.

Science.gov (United States)

Gorrepati, Lakshmi; Thompson, Kenneth W; Eisenmann, David M

2013-05-01

The C. elegans seam cells are lateral epithelial cells arrayed in a single line from anterior to posterior that divide in an asymmetric, stem cell-like manner during larval development. These asymmetric divisions are regulated by Wnt signaling; in most divisions, the posterior daughter in which the Wnt pathway is activated maintains the progenitor seam fate, while the anterior daughter in which the Wnt pathway is not activated adopts a differentiated hypodermal fate. Using mRNA tagging and microarray analysis, we identified the functionally redundant GATA factor genes egl-18 and elt-6 as Wnt pathway targets in the larval seam cells. EGL-18 and ELT-6 have previously been shown to be required for initial seam cell specification in the embryo. We show that in larval seam cell asymmetric divisions, EGL-18 is expressed strongly in the posterior seam-fated daughter. egl-18 and elt-6 are necessary for larval seam cell specification, and for hypodermal to seam cell fate transformations induced by ectopic Wnt pathway overactivation. The TCF homolog POP-1 binds a site in the egl-18 promoter in vitro, and this site is necessary for robust seam cell expression in vivo. Finally, larval overexpression of EGL-18 is sufficient to drive expression of a seam marker in other hypodermal cells in wild-type animals, and in anterior hypodermal-fated daughters in a Wnt pathway-sensitized background. These data suggest that two GATA factors that are required for seam cell specification in the embryo independently of Wnt signaling are reused downstream of Wnt signaling to maintain the progenitor fate during stem cell-like divisions in larval development.

Cultural Diversity in English Language Teaching: Learners' Voices

Science.gov (United States)

Chinh, Nguyen Duc

2013-01-01

The focus of culture in English language teaching (ELT) has traditionally been on the target culture of English speaking countries. However, the new status of English as international language (EIL) has led to significant changes in the practice of teaching and learning culture in ELT. Rather than relying on the paradigm of native speaker…

Active learning reduces annotation time for clinical concept extraction.

Science.gov (United States)

Kholghi, Mahnoosh; Sitbon, Laurianne; Zuccon, Guido; Nguyen, Anthony

2017-10-01

To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating the manual annotation process compared to de novo annotation. There are 73 and 120 discharge summary reports provided by Beth Israel institute in the train and test sets of the concept extraction task in the i2b2/VA 2010 challenge, respectively. The 73 reports were used in user study experiments for manual annotation. First, all sequences within the 73 reports were manually annotated from scratch. Next, active learning models were built to generate pre-annotations for the sequences selected by a query strategy. The annotation/reviewing time per sequence was recorded. The 120 test reports were used to measure the effectiveness of the active learning models. When annotating from scratch, active learning reduced the annotation time up to 35% and 28% compared to a fully supervised approach and a random sampling baseline, respectively. Reviewing active learning-assisted pre-annotations resulted in 20% further reduction of the annotation time when compared to de novo annotation. The number of concepts that require manual annotation is a good indicator of the annotation time for various active learning approaches as demonstrated by high correlation between time rate and concept annotation rate. Active learning has a key role in reducing the time required to manually annotate domain concepts from clinical free text, either when annotating from scratch or reviewing active learning-assisted pre-annotations. Copyright © 2017 Elsevier B.V. All rights reserved.

New frontiers in teaching and learning English

CERN Document Server

Vettorel, Paola

2015-01-01

The contributions to this volume explore several focal issues related to the global spread of English and their implications for English language teaching, providing both theoretical and empirical perspectives on recent research and implications in educational terms. The volume is divided into three thematic sections, namely ""Developments in ELF research and pedagogic implications"", ""Raising teachers' awareness of ELF"", and ""ELF and ELT practices"". The book provides up-to-date perspectives on the issues, implications and repercussions that findings in ELF research can have for ELT practi

Galaxy Mass Assembly with VLT & HST and lessons for E-ELT/MOSAIC

Science.gov (United States)

Hammer, François; Flores, Hector; Puech, Mathieu

2015-02-01

The fraction of distant disks and mergers is still debated, while 3D-spectroscopy is revolutionizing the field. However its limited spatial resolution imposes a complimentary HST imagery and a robust analysis procedure. When applied to observations of IMAGES galaxies at z = 0.4-0.8, it reveals that half of the spiral progenitors were in a merger phase, 6 billion year ago. The excellent correspondence between methodologically-based classifications of morphologies and kinematics definitively probes a violent origin of disk galaxies as proposed by Hammer et al. (2005). Examination of nearby galaxy outskirts reveals fossil imprints of such ancient merger events, under the form of well organized stellar streams. Perhaps our neighbor, M31, is the best illustration of an ancient merger, which modeling in 2010 leads to predict the gigantic plane of satellites discovered by Ibata et al. (2013). There are still a lot of discoveries to be done until the ELT era, which will open an avenue for detailed and accurate 3D-spectroscopy of galaxies from the earliest epochs to the present.

Lexical Evaluation of Teacher-Made Coursebooks: Thai Case Studies of Foundation English Courses at Tertiary Level

Science.gov (United States)

Wan-a-rom, Udorn

2012-01-01

Coursebooks as one of the major issues of language teaching/learning instruction can relieve the overburden as well as under-prepared teacher of a great deal of stress, time and additional work. Currently, both commercial and teacher-made English language teaching (ELT) coursebooks are available for use and seem flexible at hands. In any respect,…

A Model for Learning Over Time: The Big Picture

Science.gov (United States)

Amato, Herbert K.; Konin, Jeff G.; Brader, Holly

2002-01-01

Objective: To present a method of describing the concept of “learning over time” with respect to its implementation into an athletic training education program curriculum. Background: The formal process of learning over time has recently been introduced as a required way for athletic training educational competencies and clinical proficiencies to be delivered and mastered. Learning over time incorporates the documented cognitive, psychomotor, and affective skills associated with the acquisition, progression, and reflection of information. This method of academic preparation represents a move away from a quantitative-based learning module toward a proficiency-based mastery of learning. Little research or documentation can be found demonstrating either the specificity of this concept or suggestions for its application. Description: We present a model for learning over time that encompasses multiple indicators for assessment in a successive format. Based on a continuum approach, cognitive, psychomotor, and affective characteristics are assessed at different levels in classroom and clinical environments. Clinical proficiencies are a common set of entry-level skills that need to be integrated into the athletic training educational domains. Objective documentation is presented, including the skill breakdown of a task and a matrix to identify a timeline of competency and proficiency delivery. Clinical Advantages: The advantages of learning over time pertain to the integration of cognitive knowledge into clinical skill acquisition. Given the fact that learning over time has been implemented as a required concept for athletic training education programs, this model may serve to assist those program faculty who have not yet developed, or are in the process of developing, a method of administering this approach to learning. PMID:12937551

E-learning for Part-Time Medical Studies

Directory of Open Access Journals (Sweden)

Półjanowicz Wiesław

2016-12-01

Full Text Available Distance education undoubtedly has many advantages, such as individualization of the learning process, unified transmission of teaching materials, the opportunity to study at any place and any time, reduction of financial costs for commuting to classes or accommodation of participants, etc. Adequate working conditions on the e-learning portal must also be present, eg. well-prepared, substantive courses and good communication between the participants. Therefore, an important element in the process of conducting e-learning courses is to measure the increase of knowledge and satisfaction of participants with distance learning. It allows for fine-tuning the content of the course and for classes to be properly organized. This paper presents the results of teaching and assessment of satisfaction with e-learning courses in “Problems of multiculturalism in medicine”, “Selected issues of visual rehabilitation” and “Ophthalmology and Ophthalmic Nursing”, which were carried out experimentally at the Faculty of Health Sciences at the Medical University of Bialystok for nursing students for the 2010/2011 academic year. The study group consisted of 72 part-time students who learnt in e-learning mode and the control group of 87 students who learnt in the traditional way. The students’ opinions about the teaching process and final exam scores were analyzed based on a specially prepared survey questionnaire. Organization of e-learning classes was rated positively by 90% of students. The average result on the final exams for all distance learning subjects was at the level of 82%, while for classes taught in the traditional form it was 81%. Based on these results, we conclude that distance learning is as effective as learning according to the traditional form in medical education studies.

Professional Learning in Part-time University Study

DEFF Research Database (Denmark)

Rasmussen, Palle

2007-01-01

The theme of this article is adult students' learning in part-time studies at university level in Denmark. One issue discussed is the interplay of research and teaching in this kind of study programme. Examples are presented from the Master of Learning Processes study programme at Aalborg...

Final-year veterinary students' perceptions of their communication competencies and a communication skills training program delivered in a primary care setting and based on Kolb's Experiential Learning Theory.

Science.gov (United States)

Meehan, Michael P; Menniti, Marie F

2014-01-01

Veterinary graduates require effective communication skills training to successfully transition from university into practice. Although the literature has supported the need for veterinary student communication skills training programs, there is minimal research using learning theory to design programs and explore students' perceptions of such programs. This study investigated veterinary students' perceptions of (1) their communication skills and (2) the usefulness of a communication skills training program designed with Kolb's Experiential Learning Theory (ELT) as a framework and implemented in a primary care setting. Twenty-nine final-year veterinary students from the Ontario Veterinary College attended a 3-week communication skills training rotation. Pre- and post-training surveys explored their communication objectives, confidence in their communication skills, and the usefulness of specific communication training strategies. The results indicated that both before and after training, students were most confident in building rapport, displaying empathy, recognizing how bonded a client is with his or her pet, and listening. They were least confident in managing clients who were angry or not happy with the charges and who monopolized the appointment. Emotionally laden topics, such as breaking bad news and managing euthanasia discussions, were also identified as challenging and in need of improvement. Interactive small-group discussions and review of video-recorded authentic client appointments were most valuable for their learning and informed students' self-awareness of their non-verbal communication. These findings support the use of Kolb's ELT as a theoretical framework and of video review and reflection to guide veterinary students' learning of communication skills in a primary care setting.

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.

Increasing instruction time in school does increase learning

DEFF Research Database (Denmark)

Andersen, Simon Calmar; Humlum, Maria; Nandrup, Anne Brink

2016-01-01

Increasing instruction time in school is a central element in the attempts of many governments to improve student learning, but prior research—mainly based on observational data—disputes the effect of this approach and points out the potential negative effects on student behavior. Based on a large......-scale, cluster-randomized trial, we find that increasing instruction time increases student learning and that a general increase in instruction time is at least as efficient as an expert-developed, detailed teaching program that increases instruction with the same amount of time. These findings support the value...... of increased instruction time....

Real-time Color Codes for Assessing Learning Process

OpenAIRE

Dzelzkalēja, L; Kapenieks, J

2016-01-01

Effective assessment is an important way for improving the learning process. There are existing guidelines for assessing the learning process, but they lack holistic digital knowledge society considerations. In this paper the authors propose a method for real-time evaluation of students’ learning process and, consequently, for quality evaluation of teaching materials both in the classroom and in the distance learning environment. The main idea of the proposed Color code method (CCM) is to use...

Imaging extrasolar planets with the European Extremely Large Telescope

Directory of Open Access Journals (Sweden)

Jolissaint L.

2011-07-01

Full Text Available The European Extremely Large Telescope (E-ELT is the most ambitious of the ELTs being planned. With a diameter of 42 m and being fully adaptive from the start, the E-ELT will be more than one hundred times more sensitive than the present-day largest optical telescopes. Discovering and characterising planets around other stars will be one of the most important aspects of the E-ELT science programme. We model an extreme adaptive optics instrument on the E-ELT. The resulting contrast curves translate to the detectability of exoplanets.

Green FLASH: energy efficient real-time control for AO

Science.gov (United States)

Gratadour, D.; Dipper, N.; Biasi, R.; Deneux, H.; Bernard, J.; Brule, J.; Dembet, R.; Doucet, N.; Ferreira, F.; Gendron, E.; Laine, M.; Perret, D.; Rousset, G.; Sevin, A.; Bitenc, U.; Geng, D.; Younger, E.; Andrighettoni, M.; Angerer, G.; Patauner, C.; Pescoller, D.; Porta, F.; Dufourcq, G.; Flaischer, A.; Leclere, J.-B.; Nai, A.; Palazzari, P.; Pretet, D.; Rouaud, C.

2016-07-01

The main goal of Green Flash is to design and build a prototype for a Real-Time Controller (RTC) targeting the European Extremely Large Telescope (E-ELT) Adaptive Optics (AO) instrumentation. The E-ELT is a 39m diameter telescope to see first light in the early 2020s. To build this critical component of the telescope operations, the astronomical community is facing technical challenges, emerging from the combination of high data transfer bandwidth, low latency and high throughput requirements, similar to the identified critical barriers on the road to Exascale. With Green Flash, we will propose technical solutions, assess these enabling technologies through prototyping and assemble a full scale demonstrator to be validated with a simulator and tested on sky. With this R&D program we aim at feeding the E-ELT AO systems preliminary design studies, led by the selected first-light instruments consortia, with technological validations supporting the designs of their RTC modules. Our strategy is based on a strong interaction between academic and industrial partners. Components specifications and system requirements are derived from the AO application. Industrial partners lead the development of enabling technologies aiming at innovative tailored solutions with potential wide application range. The academic partners provide the missing links in the ecosystem, targeting their application with mainstream solutions. This increases both the value and market opportunities of the developed products. A prototype harboring all the features is used to assess the performance. It also provides the proof of concept for a resilient modular solution to equip a large scale European scientific facility, while containing the development cost by providing opportunities for return on investment.

Linear time relational prototype based learning.

Science.gov (United States)

Gisbrecht, Andrej; Mokbel, Bassam; Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara

2012-10-01

Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.

Learned Interval Time Facilitates Associate Memory Retrieval

Science.gov (United States)

van de Ven, Vincent; Kochs, Sarah; Smulders, Fren; De Weerd, Peter

2017-01-01

The extent to which time is represented in memory remains underinvestigated. We designed a time paired associate task (TPAT) in which participants implicitly learned cue-time-target associations between cue-target pairs and specific cue-target intervals. During subsequent memory testing, participants showed increased accuracy of identifying…

A Lecture Supporting System Based on Real-Time Learning Analytics

Science.gov (United States)

Shimada, Atsushi; Konomi, Shin'ichi

2017-01-01

A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

Human learning: Power laws or multiple characteristic time scales?

Directory of Open Access Journals (Sweden)

Gottfried Mayer-Kress

2006-09-01

Full Text Available The central proposal of A. Newell and Rosenbloom (1981 was that the power law is the ubiquitous law of learning. This proposition is discussed in the context of the key factors that led to the acceptance of the power law as the function of learning. We then outline the principles of an epigenetic landscape framework for considering the role of the characteristic time scales of learning and an approach to system identification of the processes of performance dynamics. In this view, the change of performance over time is the product of a superposition of characteristic exponential time scales that reflect the influence of different processes. This theoretical approach can reproduce the traditional power law of practice – within the experimental resolution of performance data sets - but we hypothesize that this function may prove to be a special and perhaps idealized case of learning.

An alternative approach to analyze Ipsative data. Revisiting Experiential Learning Theory

Directory of Open Access Journals (Sweden)

Joan Manuel eBatista-Foguet

2015-11-01

Full Text Available The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines. Statistical models involve a series of assumptions whose existence is often neglected altogether, thus making the mentioned common practice even more pervasive. This paper illustrates the consequences of this ritualistic practice within Kolb’s Experiential Learning Theory (ELT operationalized through its Learning Style Inventory (KLSI. We show how using a well-known methodology in other disciplines -compositional data analysis (CODA- KLSI data can be properly analyzed. In addition, a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual’s relative preference for learning by prehension rather than by transformation. Using a sample of European MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ, and with an observer-assessed instrument, the Emotional and Social Inventory (ESCI-U. Both show plausible statistical relationships. An intellectual operating philosophy is linked to a preference for prehension, whereas a pragmatic operating philosophy is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.

An Empirical Investigation of Individual Differences in Time to Learn

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Anderson, Lorin W.

1976-01-01

Results show that student differences in time-on-task to learn to criterion are alterable and can be minimized over a sequence of learning units given appropriate adaptive learning strategies. (Author/DEP)

Hierarchical Meta-Learning in Time Series Forecasting for Improved Interference-Less Machine Learning

Directory of Open Access Journals (Sweden)

David Afolabi

2017-11-01

Full Text Available The importance of an interference-less machine learning scheme in time series prediction is crucial, as an oversight can have a negative cumulative effect, especially when predicting many steps ahead of the currently available data. The on-going research on noise elimination in time series forecasting has led to a successful approach of decomposing the data sequence into component trends to identify noise-inducing information. The empirical mode decomposition method separates the time series/signal into a set of intrinsic mode functions ranging from high to low frequencies, which can be summed up to reconstruct the original data. The usual assumption that random noises are only contained in the high-frequency component has been shown not to be the case, as observed in our previous findings. The results from that experiment reveal that noise can be present in a low frequency component, and this motivates the newly-proposed algorithm. Additionally, to prevent the erosion of periodic trends and patterns within the series, we perform the learning of local and global trends separately in a hierarchical manner which succeeds in detecting and eliminating short/long term noise. The algorithm is tested on four datasets from financial market data and physical science data. The simulation results are compared with the conventional and state-of-the-art approaches for time series machine learning, such as the non-linear autoregressive neural network and the long short-term memory recurrent neural network, respectively. Statistically significant performance gains are recorded when the meta-learning algorithm for noise reduction is used in combination with these artificial neural networks. For time series data which cannot be decomposed into meaningful trends, applying the moving average method to create meta-information for guiding the learning process is still better than the traditional approach. Therefore, this new approach is applicable to the forecasting

Real-time individualized training vectors for experiential learning.

Energy Technology Data Exchange (ETDEWEB)

Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie; Glickman, Matthew R.; Fabian, Nathan

2011-01-01

Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD) project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.

Interview with Alan Maley on Teaching and Learning Creative Writing

Directory of Open Access Journals (Sweden)

Ruzbeh Babaee

2015-07-01

Full Text Available Alan Maley is a British, award-winning, internationally-known writer and artist, highly regarded for his unique observation of life at the turn of the century. He has been involved in English Language Teaching (ELT for over 50 years. He worked for the British Council in Yugoslavia, Ghana, Italy, France, China and India and was the Director of the Bell Educational Trust in Cambridge for 5 years. He later worked in universities in Singapore, Thailand, Malaysia and UK. Alan has published over 40 books and numerous articles. In the following, Dr. Maley answered our questions on teaching creative writing in academic centers, the relationship between creative writing and language learning, and the status of creative writing in non-English speaking countries.

Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

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Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping

2012-05-01

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

The evolutionary duplication and probable demise of an endodermal GATA factor in Caenorhabditis elegans.

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Fukushige, Tetsunari; Goszczynski, Barbara; Tian, Helen; McGhee, James D

2003-10-01

We describe the elt-4 gene from the nematode Caenorhabditis elegans. elt-4 is predicted to encode a very small (72 residues, 8.1 kD) GATA-type zinc finger transcription factor. The elt-4 gene is located approximately 5 kb upstream of the C. elegans elt-2 gene, which also encodes a GATA-type transcription factor; the zinc finger DNA-binding domains are highly conserved (24/25 residues) between the two proteins. The elt-2 gene is expressed only in the intestine and is essential for normal intestinal development. This article explores whether elt-4 also has a role in intestinal development. Reporter fusions to the elt-4 promoter or reporter insertions into the elt-4 coding regions show that elt-4 is indeed expressed in the intestine, beginning at the 1.5-fold stage of embryogenesis and continuing into adulthood. elt-4 reporter fusions are also expressed in nine cells of the posterior pharynx. Ectopic expression of elt-4 cDNA within the embryo does not cause detectable ectopic expression of biochemical markers of gut differentiation; furthermore, ectopic elt-4 expression neither inhibits nor enhances the ectopic marker expression caused by ectopic elt-2 expression. A deletion allele of elt-4 was isolated but no obvious phenotype could be detected, either in the gut or elsewhere; brood sizes, hatching efficiencies, and growth rates were indistinguishable from wild type. We found no evidence that elt-4 provided backup functions for elt-2. We used microarray analysis to search for genes that might be differentially expressed between L1 larvae of the elt-4 deletion strain and wild-type worms. Paired hybridizations were repeated seven times, allowing us to conclude, with some confidence, that no candidate target transcript could be identified as significantly up- or downregulated by loss of elt-4 function. In vitro binding experiments could not detect specific binding of ELT-4 protein to candidate binding sites (double-stranded oligonucleotides containing single or multiple

Time to rethink the neural mechanisms of learning and memory.

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Gallistel, Charles R; Balsam, Peter D

2014-02-01

Most studies in the neurobiology of learning assume that the underlying learning process is a pairing - dependent change in synaptic strength that requires repeated experience of events presented in close temporal contiguity. However, much learning is rapid and does not depend on temporal contiguity, which has never been precisely defined. These points are well illustrated by studies showing that the temporal relations between events are rapidly learned- even over long delays- and that this knowledge governs the form and timing of behavior. The speed with which anticipatory responses emerge in conditioning paradigms is determined by the information that cues provide about the timing of rewards. The challenge for understanding the neurobiology of learning is to understand the mechanisms in the nervous system that encode information from even a single experience, the nature of the memory mechanisms that can encode quantities such as time, and how the brain can flexibly perform computations based on this information. Copyright © 2013 Elsevier Inc. All rights reserved.

On learning science and pseudoscience from prime-time television programming

Science.gov (United States)

Whittle, Christopher Henry

The purpose of the present dissertation is to determine whether the viewing of two particular prime-time television programs, ER and The X-Files, increases viewer knowledge of science and to identify factors that may influence learning from entertainment television programming. Viewer knowledge of scientific dialogue from two science-based prime-time television programs, ER, a serial drama in a hospital emergency room and The X-Files, a drama about two Federal Bureau of Investigation agents who pursue alleged extraterrestrial life and paranormal activity, is studied. Level of viewing, education level, science education level, experiential factors, level of parasocial interaction, and demographic characteristics are assessed as independent variables affecting learning from entertainment television viewing. The present research involved a nine-month long content analysis of target television program dialogue and data collection from an Internet-based survey questionnaire posted to target program-specific on-line "chat" groups. The present study demonstrated that entertainment television program viewers incidentally learn science from entertainment television program dialogue. The more they watch, the more they learn. Viewing a pseudoscientific fictional television program does necessarily influence viewer beliefs in pseudoscience. Higher levels of formal science study are reflected in more science learning and less learning of pseudoscience from entertainment television program viewing. Pseudoscience learning from entertainment television programming is significantly related to experience with paranormal phenomena, higher levels of viewer parasocial interaction, and specifically, higher levels of cognitive parasocial interaction. In summary, the greater a viewer's understanding of science the more they learn when they watch their favorite science-based prime-time television programs. Viewers of pseudoscience-based prime-time television programming with higher levels

A presentation system for just-in-time learning in radiology.

Science.gov (United States)

Kahn, Charles E; Santos, Amadeu; Thao, Cheng; Rock, Jayson J; Nagy, Paul G; Ehlers, Kevin C

2007-03-01

There is growing interest in bringing medical educational materials to the point of care. We sought to develop a system for just-in-time learning in radiology. A database of 34 learning modules was derived from previously published journal articles. Learning objectives were specified for each module, and multiple-choice test items were created. A web-based system-called TEMPO-was developed to allow radiologists to select and view the learning modules. Web services were used to exchange clinical context information between TEMPO and the simulated radiology work station. Preliminary evaluation was conducted using the System Usability Scale (SUS) questionnaire. TEMPO identified learning modules that were relevant to the age, sex, imaging modality, and body part or organ system of the patient being viewed by the radiologist on the simulated clinical work station. Users expressed a high degree of satisfaction with the system's design and user interface. TEMPO enables just-in-time learning in radiology, and can be extended to create a fully functional learning management system for point-of-care learning in radiology.

Nuclear power plant monitoring using real-time learning neural network

International Nuclear Information System (INIS)

Nabeshima, Kunihiko; Tuerkcan, E.; Ciftcioglu, O.

1994-01-01

In the present research, artificial neural network (ANN) with real-time adaptive learning is developed for the plant wide monitoring of Borssele Nuclear Power Plant (NPP). Adaptive ANN learning capability is integrated to the monitoring system so that robust and sensitive on-line monitoring is achieved in real-time environment. The major advantages provided by ANN are that system modelling is formed by means of measurement information obtained from a multi-output process system, explicit modelling is not required and the modelling is not restricted to linear systems. Also ANN can respond very fast to anomalous operational conditions. The real-time ANN learning methodology with adaptive real-time monitoring capability is described below for the wide-range and plant-wide data from an operating nuclear power plant. The layered neural network with error backpropagation algorithm for learning has three layers. The network type is auto-associative, inputs and outputs are exactly the same, using 12 plant signals. (author)

Effect of chronotype and student learning time on mathematical ability based on self-regulated learning

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Ratnaningsih, N.; El Akbar, R. R.; Hidayat, E.

2018-05-01

One of ways to improve students' learning ability is conduct a research, with purpose to obtain a method to improve students' ability. Research often carried out on the modification of teaching methods, uses of teaching media, motivation, interests and talents of students. Research related to the internal condition of students becomes very interesting to studied, including research on circadian rhythms. Every person in circadian rhythms has its own Chronotype, which divided into two types namely early type and night late type. Chronotype affects the comfort in activity, for example a person with Chronotype category of early type tends to be more comfort in daytime activities. The purpose of this study is to examine the conditions of students, related Chronotype suitable or appropriate for student learning time. This suitability then studied in relation to the ability of learning mathematics with self- regulated learning approach. This study consists of three stages; (i) student Chronotype measurement, (ii) data retrieval, and (iii) analysis of research results. The results show the relationship between the students' learning ability in mathematics to learning time corresponding to Chronotype.

In real time: exploring nursing students' learning during an international experience.

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Afriyie Asenso, Barbara; Reimer-Kirkham, Sheryl; Astle, Barbara

2013-10-11

Abstract Nursing education has increasingly turned to international learning experiences to educate students who are globally minded and aware of social injustices in local and global communities. To date, research with international learning experiences has focused on the benefits for the students participating, after they have completed the international experience. The purpose of this qualitative study was to explore how nursing students learn during the international experience. The sample consisted of eight nursing students who enrolled in an international learning experience, and data were collected in "real time" in Zambia. The students were observed during learning activities and were interviewed three times. Three major themes emerged from the thematic analysis: expectations shaped students' learning, engagement facilitated learning, and critical reflection enhanced learning. Implications are discussed, related to disrupting media representations of Africa that shape students' expectations, and educational strategies for transformative learning and global citizenship.

Towards Real-Time Speech Emotion Recognition for Affective E-Learning

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Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

2016-01-01

This paper presents the voice emotion recognition part of the FILTWAM framework for real-time emotion recognition in affective e-learning settings. FILTWAM (Framework for Improving Learning Through Webcams And Microphones) intends to offer timely and appropriate online feedback based upon learner's vocal intonations and facial expressions in order…

Time representation in reinforcement learning models of the basal ganglia

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Samuel Joseph Gershman

2014-01-01

Full Text Available Reinforcement learning models have been influential in understanding many aspects of basal ganglia function, from reward prediction to action selection. Time plays an important role in these models, but there is still no theoretical consensus about what kind of time representation is used by the basal ganglia. We review several theoretical accounts and their supporting evidence. We then discuss the relationship between reinforcement learning models and the timing mechanisms that have been attributed to the basal ganglia. We hypothesize that a single computational system may underlie both reinforcement learning and interval timing—the perception of duration in the range of seconds to hours. This hypothesis, which extends earlier models by incorporating a time-sensitive action selection mechanism, may have important implications for understanding disorders like Parkinson's disease in which both decision making and timing are impaired.

Rewiring Warfighters for Joint Mindedness: Solutions for Joint Education in the 21st Century

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2010-06-01

eventually make symmetry the norm), the author will demonstrate how Experiential Learning Theory provides a mechanism to correct perception through...firsthand and then analyzes objectively the merits of each service’s capability. Experiential Learning Theory (ELT) is "a four staged cyclical...39 David Kolb . Experiential Learning : Experience as the Source of Learning and Development. (Englewood

Understanding the effects of time on collaborative learning processes in problem based learning: a mixed methods study.

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Hommes, J; Van den Bossche, P; de Grave, W; Bos, G; Schuwirth, L; Scherpbier, A

2014-10-01

Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning processes developed within and over three periods in the first 1,5 study years of an undergraduate curriculum. Next, a qualitative study using semi-structured individual interviews focused on detailed development of group processes driving collaborative learning during one period in seven tutorial groups. The hierarchic multilevel analyses of the quantitative data showed that a varying combination of group processes developed within and over the three observed periods. The qualitative study illustrated development in psychological safety, interdependence, potency, group learning behaviour, social and task cohesion. Two new processes emerged: 'transactive memory' and 'convergence in mental models'. The results indicate that groups are dynamic social systems with numerous contextual influences. Future research should thus include time as an important influence on collaborative learning. Practical implications are discussed.

Adaptation and learning: characteristic time scales of performance dynamics.

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Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

Bilingualism--A Sanguine Step in ELT

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Anil, Beena

2014-01-01

Bilingualism can be used as a teaching aid in teaching and learning English language in an Indian classroom and to improve the language accuracy, fluency, and clarity of learners. Bilingualism can aid the teaching and learning process productively in the classroom. In India, most of the students consider English as a subject rather than a tool of…

Dissociable effects of practice variability on learning motor and timing skills.

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Caramiaux, Baptiste; Bevilacqua, Frédéric; Wanderley, Marcelo M; Palmer, Caroline

2018-01-01

Motor skill acquisition inherently depends on the way one practices the motor task. The amount of motor task variability during practice has been shown to foster transfer of the learned skill to other similar motor tasks. In addition, variability in a learning schedule, in which a task and its variations are interweaved during practice, has been shown to help the transfer of learning in motor skill acquisition. However, there is little evidence on how motor task variations and variability schedules during practice act on the acquisition of complex motor skills such as music performance, in which a performer learns both the right movements (motor skill) and the right time to perform them (timing skill). This study investigated the impact of rate (tempo) variability and the schedule of tempo change during practice on timing and motor skill acquisition. Complete novices, with no musical training, practiced a simple musical sequence on a piano keyboard at different rates. Each novice was assigned to one of four learning conditions designed to manipulate the amount of tempo variability across trials (large or small tempo set) and the schedule of tempo change (randomized or non-randomized order) during practice. At test, the novices performed the same musical sequence at a familiar tempo and at novel tempi (testing tempo transfer), as well as two novel (but related) sequences at a familiar tempo (testing spatial transfer). We found that practice conditions had little effect on learning and transfer performance of timing skill. Interestingly, practice conditions influenced motor skill learning (reduction of movement variability): lower temporal variability during practice facilitated transfer to new tempi and new sequences; non-randomized learning schedule improved transfer to new tempi and new sequences. Tempo (rate) and the sequence difficulty (spatial manipulation) affected performance variability in both timing and movement. These findings suggest that there is a

EFL Teachers’ Perceptions of The Place of Culture in ELT: A Survey Study at Four Universities in Ankara/Turkey

Directory of Open Access Journals (Sweden)

Okan ÖNALAN

2005-10-01

Full Text Available This study aims to investigate Turkish teachers’ opinions and beliefs on the place of target cultural information in English language teaching, as well as their related practices andapplications in EFL classrooms in Turkish higher education context. Particularly, it tries toexplore three research questions: (a How do Turkish teachers of English define culture? (bWhat are the EFL teachers’ attitudes towards incorporating cultural information into theirteaching? and (c What role do they allocate to the culture of the target language in theirclassrooms? The study shows that teachers mostly define culture in the sociological sense, suchas values and beliefs. Their definition of culture in the framework of ELT slightly shifts towardsmore visible culture, such as food and clothing. The study also reveals teachers’ positive attitudestowards incorporating cultural information in their instruction.

A novel time series link prediction method: Learning automata approach

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Moradabadi, Behnaz; Meybodi, Mohammad Reza

2017-09-01

Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

An Alternative Approach to Analyze Ipsative Data. Revisiting Experiential Learning Theory.

Science.gov (United States)

Batista-Foguet, Joan M; Ferrer-Rosell, Berta; Serlavós, Ricard; Coenders, Germà; Boyatzis, Richard E

2015-01-01

The ritualistic use of statistical models regardless of the type of data actually available is a common practice across disciplines which we dare to call type zero error. Statistical models involve a series of assumptions whose existence is often neglected altogether, this is specially the case with ipsative data. This paper illustrates the consequences of this ritualistic practice within Kolb's Experiential Learning Theory (ELT) operationalized through its Learning Style Inventory (KLSI). We show how using a well-known methodology in other disciplines-compositional data analysis (CODA) and log ratio transformations-KLSI data can be properly analyzed. In addition, the method has theoretical implications: a third dimension of the KLSI is unveiled providing room for future research. This third dimension describes an individual's relative preference for learning by prehension rather than by transformation. Using a sample of international MBA students, we relate this dimension with another self-assessment instrument, the Philosophical Orientation Questionnaire (POQ), and with an observer-assessed instrument, the Emotional and Social Competency Inventory (ESCI-U). Both show plausible statistical relationships. An intellectual operating philosophy (IOP) is linked to a preference for prehension, whereas a pragmatic operating philosophy (POP) is linked to transformation. Self-management and social awareness competencies are linked to a learning preference for transforming knowledge, whereas relationship management and cognitive competencies are more related to approaching learning by prehension.

Learning Styles of Medical Students Change in Relation to Time

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Gurpinar, Erol; Bati, Hilal; Tetik, Cihat

2011-01-01

The aim of the present study was to investigate if any changes exist in the learning styles of medical students over time and in relation to different curriculum models with these learning styles. This prospective cohort study was conducted in three different medical faculties, which implement problem-based learning (PBL), hybrid, and integrated…

Generalization bounds of ERM-based learning processes for continuous-time Markov chains.

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Zhang, Chao; Tao, Dacheng

2012-12-01

Many existing results on statistical learning theory are based on the assumption that samples are independently and identically distributed (i.i.d.). However, the assumption of i.i.d. samples is not suitable for practical application to problems in which samples are time dependent. In this paper, we are mainly concerned with the empirical risk minimization (ERM) based learning process for time-dependent samples drawn from a continuous-time Markov chain. This learning process covers many kinds of practical applications, e.g., the prediction for a time series and the estimation of channel state information. Thus, it is significant to study its theoretical properties including the generalization bound, the asymptotic convergence, and the rate of convergence. It is noteworthy that, since samples are time dependent in this learning process, the concerns of this paper cannot (at least straightforwardly) be addressed by existing methods developed under the sample i.i.d. assumption. We first develop a deviation inequality for a sequence of time-dependent samples drawn from a continuous-time Markov chain and present a symmetrization inequality for such a sequence. By using the resultant deviation inequality and symmetrization inequality, we then obtain the generalization bounds of the ERM-based learning process for time-dependent samples drawn from a continuous-time Markov chain. Finally, based on the resultant generalization bounds, we analyze the asymptotic convergence and the rate of convergence of the learning process.

DeepRT: deep learning for peptide retention time prediction in proteomics

OpenAIRE

Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

2017-01-01

Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses.

Science.gov (United States)

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito

2015-12-01

We propose a supervised learning model that enables error backpropagation for spiking neural network hardware. The method is modeled by modifying an existing model to suit the hardware implementation. An example of a network circuit for the model is also presented. In this circuit, a three-terminal ferroelectric memristor (3T-FeMEM), which is a field-effect transistor with a gate insulator composed of ferroelectric materials, is used as an electric synapse device to store the analog synaptic weight. Our model can be implemented by reflecting the network error to the write voltage of the 3T-FeMEMs and introducing a spike-timing-dependent learning function to the device. An XOR problem was successfully demonstrated as a benchmark learning by numerical simulations using the circuit properties to estimate the learning performance. In principle, the learning time per step of this supervised learning model and the circuit is independent of the number of neurons in each layer, promising a high-speed and low-power calculation in large-scale neural networks.

Understanding the Effects of Time on Collaborative Learning Processes in Problem Based Learning: A Mixed Methods Study

Science.gov (United States)

Hommes, J.; Van den Bossche, P.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.

2014-01-01

Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning…

Time and Associative Learning.

Science.gov (United States)

Balsam, Peter D; Drew, Michael R; Gallistel, C R

2010-01-01

In a basic associative learning paradigm, learning is said to have occurred when the conditioned stimulus evokes an anticipatory response. This learning is widely believed to depend on the contiguous presentation of conditioned and unconditioned stimulus. However, what it means to be contiguous has not been rigorously defined. Here we examine the empirical bases for these beliefs and suggest an alternative view based on the hypothesis that learning about the temporal relationships between events determines the speed of emergence, vigor and form of conditioned behavior. This temporal learning occurs very rapidly and prior to the appearance of the anticipatory response. The temporal relations are learned even when no anticipatory response is evoked. The speed with which an anticipatory response emerges is proportional to the informativeness of the predictive cue (CS) regarding the rate of occurrence of the predicted event (US). This analysis gives an account of what we mean by "temporal pairing" and is in accord with the data on speed of acquisition and basic findings in the cue competition literature. In this account, learning depends on perceiving and encoding temporal regularities rather than stimulus contiguities.

Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Årup; Frutiger, Sally A.

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel...... practice-related activity in a fronto-parieto-cerebellar network, in agreement with previous studies of motor learning. These voxels were separated from a group of voxels showing an unspecific time-effect and another group of voxels, whose activation was an artifact from smoothing. Hum. Brain Mapping 15...

Trip Travel Time Forecasting Based on Selective Forgetting Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Zhiming Gui

2014-01-01

Full Text Available Travel time estimation on road networks is a valuable traffic metric. In this paper, we propose a machine learning based method for trip travel time estimation in road networks. The method uses the historical trip information extracted from taxis trace data as the training data. An optimized online sequential extreme machine, selective forgetting extreme learning machine, is adopted to make the prediction. Its selective forgetting learning ability enables the prediction algorithm to adapt to trip conditions changes well. Experimental results using real-life taxis trace data show that the forecasting model provides an effective and practical way for the travel time forecasting.

Evaluating Experiential Leader Development: A Programmatic Evaluation and Comparison of the Effectiveness of US Air Force Squadron Officer School Curricula

Science.gov (United States)

2008-03-01

effectiveness as a corporate training tool has been in debate since (Weigand, 1995). Experiential Learning Theory In 1975, David Kolb attempted to...82    ix List of Figures Page 1. Kolb’s Experiential Learning Theory ...to Kolb’s (1984) experiential learning theory (ELT), the dualistic approach to knowledge acquisition and transformation taken by these programs

Exploring International Student Orientation and Attitude towards Learning English in Malaysia

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Ayesha Abdullah Najieb Badib

2011-07-01

Full Text Available The Malaysian government is rigorously drawing up strategies to increase the already existing 60,000 foreign students currently studying in the country (The Star, 2009. With the influx of more foreign students and with English as the medium of instruction in local higher aspects that drive and/or deter them in learning English would be beneficial. The sample for this study (N=115 comprised of international students from China, Iran, Kazakhstan, Indonesia, Korea, Vietnam, Maldives and the Middle East undertaking an Intensive English course at a local private college. Data collection was done via questionnaire which was designed based on a review of existing instruments in the field. Results show that orientation towards learning English does not vary according to nationality and gender; however, students from China and Korea tend to be more inclined towards instrumental orientation, while students from Kazakhstan and Iran are more inclined towards integrative orientation. Based on the findings, this paper also proffers recommendations for local higher education institutions to enhance ELT practices for incoming international students.

Gender Representation under Critical Image Analysis: The Case of Iranian ELT Textbooks

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Ali Dabbagh

2016-12-01

Full Text Available This paper aimed to identify and reveal gender positioning in the images used in the recent ELT nation-wide text books, i.e. Prospects 1, 2 & 3. To do so, the dimensions in Goffman (1976 were mixed with the image semiotic category of Kress and van Leeuwen (2006 to analyze the images in terms of determining active participant, gaze direction, visual techniques, body display, and the space in which the participants were shown. In order to elicit the hidden patterns, the data went over a thorough content analysis which revealed the following: First, males were presented more than females as active, looking at the viewer, and framed in a close–up format which signified their prominence and power in relation to females. Second, while both men and women were represented as fully clothed, no female character in the images were depicted in sparsely and lightly clothed. Third, a balanced representation was shown regarding the location in which males or females were present in the images, portraying at both home and workplace spaces despite not showing females in images related to open spaces such as streets and neighborhoods. Results promise implications for language teachers and teacher educators as to raise their awareness of gender bias, though in some aspects and not in others, in images of the text books. In addition, results have clear message for material developers not to selectively represent a gender-unbiased picture of males and females in only some limited aspects.

Time course influences transfer of visual perceptual learning across spatial location.

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Larcombe, S J; Kennard, C; Bridge, H

2017-06-01

Visual perceptual learning describes the improvement of visual perception with repeated practice. Previous research has established that the learning effects of perceptual training may be transferable to untrained stimulus attributes such as spatial location under certain circumstances. However, the mechanisms involved in transfer have not yet been fully elucidated. Here, we investigated the effect of altering training time course on the transferability of learning effects. Participants were trained on a motion direction discrimination task or a sinusoidal grating orientation discrimination task in a single visual hemifield. The 4000 training trials were either condensed into one day, or spread evenly across five training days. When participants were trained over a five-day period, there was transfer of learning to both the untrained visual hemifield and the untrained task. In contrast, when the same amount of training was condensed into a single day, participants did not show any transfer of learning. Thus, learning time course may influence the transferability of perceptual learning effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

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Lun Zhai

2014-01-01

Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

Cross-cultural Communication and ELT in China

Institute of Scientific and Technical Information of China (English)

ChengTongchun

2004-01-01

Culture plays a significant role in teaching and learning a language. The acquisition of cultural knowledge is an indispensable part of language learning. This paper discusses the importance and necessity of cross-cultural communication in the language teaching, and focuses on three parts:

Improved E-ELT subsystem and component specifications, thanks to M1 test facility

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Dimmler, M.; Marrero, J.; Leveque, S.; Barriga, Pablo; Sedghi, B.; Kornweibel, N.

2014-07-01

During the last 2 years ESO has operated the "M1 Test Facility", a test stand consisting of a representative section of the E-ELT primary mirror equipped with 4 complete prototype segment subunits including sensors, actuators and control system. The purpose of the test facility is twofold: it serves to study and get familiar with component and system aspects like calibration, alignment and handling procedures and suitable control strategies on real hardware long before the primary mirror (hereafter M1) components are commissioned. Secondly, and of major benefit to the project, it offered the possibility to evaluate component and subsystem performance and interface issues in a system context in such detail, that issues could be identified early enough to feed back into the subsystem and component specifications. This considerably reduces risk and cost of the production units and allows refocusing the project team on important issues for the follow-up of the production contracts. Experiences are presented in which areas the results of the M1 Test Facility particularly helped to improve subsystem specifications and areas, where additional tests were adopted independent of the main test facility. Presented are the key experiences of the M1 Test Facility which lead to improved specifications or identified the need for additional testing outside of the M1 Test Facility.

Learning of pitch and time structures in an artificial grammar setting.

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Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Impact of Students' Temporal Perspectives on Time-on-Task and Learning Performance in Game Based Learning

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Romero, Margarida; Usart, Mireia

2013-01-01

The use of games for educational purposes has been considered as a learning methodology that attracts the students' attention and may allow focusing individuals on the learning activity through the [serious games] SG game dynamic. Based on the hypothesis that students' Temporal Perspective has an impact on learning performance and time-on-task,…

Integrated Logistics Support approach: concept for the new big projects: E-ELT, SKA, CTA

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Marchiori, G.; Rampini, F.; Formentin, F.

2014-08-01

The Integrated Logistic Support is a process supporting strategies and optimizing activities for a correct project management and system engineering development. From the design & engineering of complex technical systems, to the erection on site, acceptance and after-sales service, EIE GROUP covers all aspects of the Integrated Logistics Support (ILS) process that includes: costing process centered around the life cycle cost and Level of Repair Analyses; engineering process which influences the design via means of reliability, modularization, etc.; technical publishing process based on international specifications; ordering administration process for supply support. Through the ILS, EIE GROUP plans and directs the identification and development of logistics support and system requirements for its products, with the goal of creating systems that last longer and require less support, thereby reducing costs and increasing return on investments. ILS therefore, addresses these aspects of supportability not only during acquisition, but also throughout the operational life cycle of the system. The impact of the ILS is often measured in terms of metrics such as reliability, availability, maintainability and testability (RAMT), and System Safety (RAMS). Example of the criteria and approach adopted by EIE GROUP during the design, manufacturing and test of the ALMA European Antennas and during the design phase of the E-ELT telescope and Dome are presented.

CORRELATION OF INTEREST TO LEARN AND USE TIME LEARNING WITH LEARNING ACHIEVEMENT AUTOMOTIVE ELECTRICAL IN CLASS XII LIGHT VEHICLE ENGINEERING SMK PIRI I YOGYAKARTA ACADEMIC YEAR 2013/2014

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Ari Pujiatmoko

2014-06-01

Full Text Available The purpose of this study were: 1 to determine whether there is a correlation between students' interest in learning and the learning achievement of automotive electrical, 2 to determine whether there is a correlation between the use of time studying the learning achievement of automotive electrical, 3 to determine whether there is a correlation between student interest and use the time to learn and the learning achievement of students of class XII automotive electrical TKR SMK PIRI 1 Yogyakarta academic year 2013/2014.  This research was conducted in class XII TKR SMK PIRI 1 Yogyakarta academic year 2013/2014. This study is an ex-post facto. This study used two independent variables and the interest in learning the use of learning time, while the dependent variable is the electrical automotive learning achievement. This study is a population study by the respondent amounted to 100 students. Techniques of data collection using questionnaire techniques and engineering documentation. Research instrument in this study is a questionnaire interest in learning, inquiry learning time management and documentation of student achievement. Trials using the instrument validity and reliability test. The analysis technique used is the prerequisite test for normality, linearity, and multicollinearity. Then test hypotheses using partial correlation analysis techniques and correlation.  The results showed that: 1 students' interest to have a strong positive correlation with school performance automotive electrical ρ value of 0.737; 2 the use of learning time have a low positive correlation with school performance automotive electrical ρ value of 0.275; 3 interest student learning and the use of study time has a very strong positive correlation with learning achievement of students of class XII automotive electrical TKR SMK PIRI I Yogyakarta academic year 2013/2014 as evidenced by the value of R = 0.811.

The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

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Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

2017-01-01

Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…

Learning of time series through neuron-to-neuron instruction

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Miyazaki, Y [Department of Physics, Kyoto University, Kyoto 606-8502, (Japan); Kinzel, W [Institut fuer Theoretische Physik, Universitaet Wurzburg, 97074 Wurzburg (Germany); Shinomoto, S [Department of Physics, Kyoto University, Kyoto (Japan)

2003-02-07

A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space.

Learning of time series through neuron-to-neuron instruction

International Nuclear Information System (INIS)

Miyazaki, Y; Kinzel, W; Shinomoto, S

2003-01-01

A model neuron with delayline feedback connections can learn a time series generated by another model neuron. It has been known that some student neurons that have completed such learning under the instruction of a teacher's quasi-periodic sequence mimic the teacher's time series over a long interval, even after instruction has ceased. We found that in addition to such faithful students, there are unfaithful students whose time series eventually diverge exponentially from that of the teacher. In order to understand the circumstances that allow for such a variety of students, the orbit dimension was estimated numerically. The quasi-periodic orbits in question were found to be confined in spaces with dimensions significantly smaller than that of the full phase space

Time for Learning: An Exploratory Analysis of NAEP Data

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Ginsburg, Alan; Chudowsky, Naomi

2012-01-01

This report uses NAEP background data to track time and learning since the mid-1990s in three areas: student absenteeism; classroom instructional time in mathematics, reading, music and the visual arts; and homework time expected by teachers. Key report findings are: (1) Students with higher rates of "monthly absenteeism" score…

Benefits for Voice Learning Caused by Concurrent Faces Develop over Time.

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Zäske, Romi; Mühl, Constanze; Schweinberger, Stefan R

2015-01-01

Recognition of personally familiar voices benefits from the concurrent presentation of the corresponding speakers' faces. This effect of audiovisual integration is most pronounced for voices combined with dynamic articulating faces. However, it is unclear if learning unfamiliar voices also benefits from audiovisual face-voice integration or, alternatively, is hampered by attentional capture of faces, i.e., "face-overshadowing". In six study-test cycles we compared the recognition of newly-learned voices following unimodal voice learning vs. bimodal face-voice learning with either static (Exp. 1) or dynamic articulating faces (Exp. 2). Voice recognition accuracies significantly increased for bimodal learning across study-test cycles while remaining stable for unimodal learning, as reflected in numerical costs of bimodal relative to unimodal voice learning in the first two study-test cycles and benefits in the last two cycles. This was independent of whether faces were static images (Exp. 1) or dynamic videos (Exp. 2). In both experiments, slower reaction times to voices previously studied with faces compared to voices only may result from visual search for faces during memory retrieval. A general decrease of reaction times across study-test cycles suggests facilitated recognition with more speaker repetitions. Overall, our data suggest two simultaneous and opposing mechanisms during bimodal face-voice learning: while attentional capture of faces may initially impede voice learning, audiovisual integration may facilitate it thereafter.

Estimating the implicit component of visuomotor rotation learning by constraining movement preparation time.

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Leow, Li-Ann; Gunn, Reece; Marinovic, Welber; Carroll, Timothy J

2017-08-01

When sensory feedback is perturbed, accurate movement is restored by a combination of implicit processes and deliberate reaiming to strategically compensate for errors. Here, we directly compare two methods used previously to dissociate implicit from explicit learning on a trial-by-trial basis: 1 ) asking participants to report the direction that they aim their movements, and contrasting this with the directions of the target and the movement that they actually produce, and 2 ) manipulating movement preparation time. By instructing participants to reaim without a sensory perturbation, we show that reaiming is possible even with the shortest possible preparation times, particularly when targets are narrowly distributed. Nonetheless, reaiming is effortful and comes at the cost of increased variability, so we tested whether constraining preparation time is sufficient to suppress strategic reaiming during adaptation to visuomotor rotation with a broad target distribution. The rate and extent of error reduction under preparation time constraints were similar to estimates of implicit learning obtained from self-report without time pressure, suggesting that participants chose not to apply a reaiming strategy to correct visual errors under time pressure. Surprisingly, participants who reported aiming directions showed less implicit learning according to an alternative measure, obtained during trials performed without visual feedback. This suggests that the process of reporting can affect the extent or persistence of implicit learning. The data extend existing evidence that restricting preparation time can suppress explicit reaiming and provide an estimate of implicit visuomotor rotation learning that does not require participants to report their aiming directions. NEW & NOTEWORTHY During sensorimotor adaptation, implicit error-driven learning can be isolated from explicit strategy-driven reaiming by subtracting self-reported aiming directions from movement directions, or

Time Spent, Workload, and Student and Faculty Perceptions in a Blended Learning Environment

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Schumacher, Christie; Arif, Sally

2016-01-01

Objective. To evaluate student perception and time spent on asynchronous online lectures in a blended learning environment (BLE) and to assess faculty workload and perception. Methods. Students (n=427) time spent viewing online lectures was measured in three courses. Students and faculty members completed a survey to assess perceptions of a BLE. Faculty members recorded time spent creating BLEs. Results. Total time spent in the BLE was less than the allocated time for two of the three courses by 3-15%. Students preferred online lectures for their flexibility, students’ ability to apply information learned, and congruence with their learning styles. Faculty members reported the BLE facilitated higher levels of learning during class sessions but noted an increase in workload. Conclusion. A BLE increased faculty workload but was well received by students. Time spent viewing online lectures was less than what was allocated in two of the three courses. PMID:27667839

Modeling Time Series Data for Supervised Learning

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Baydogan, Mustafa Gokce

2012-01-01

Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

Multiple transcription factors directly regulate Hox gene lin-39 expression in ventral hypodermal cells of the C. elegans embryo and larva, including the hypodermal fate regulators LIN-26 and ELT-6.

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Liu, Wan-Ju; Reece-Hoyes, John S; Walhout, Albertha J M; Eisenmann, David M

2014-05-13

Hox genes encode master regulators of regional fate specification during early metazoan development. Much is known about the initiation and regulation of Hox gene expression in Drosophila and vertebrates, but less is known in the non-arthropod invertebrate model system, C. elegans. The C. elegans Hox gene lin-39 is required for correct fate specification in the midbody region, including the Vulval Precursor Cells (VPCs). To better understand lin-39 regulation and function, we aimed to identify transcription factors necessary for lin-39 expression in the VPCs, and in particular sought factors that initiate lin-39 expression in the embryo. We used the yeast one-hybrid (Y1H) method to screen for factors that bound to 13 fragments from the lin-39 region: twelve fragments contained sequences conserved between C. elegans and two other nematode species, while one fragment was known to drive reporter gene expression in the early embryo in cells that generate the VPCs. Sixteen transcription factors that bind to eight lin-39 genomic fragments were identified in yeast, and we characterized several factors by verifying their physical interactions in vitro, and showing that reduction of their function leads to alterations in lin-39 levels and lin-39::GFP reporter expression in vivo. Three factors, the orphan nuclear hormone receptor NHR-43, the hypodermal fate regulator LIN-26, and the GATA factor ELT-6 positively regulate lin-39 expression in the embryonic precursors to the VPCs. In particular, ELT-6 interacts with an enhancer that drives GFP expression in the early embryo, and the ELT-6 site we identified is necessary for proper embryonic expression. These three factors, along with the factors ZTF-17, BED-3 and TBX-9, also positively regulate lin-39 expression in the larval VPCs. These results significantly expand the number of factors known to directly bind and regulate lin-39 expression, identify the first factors required for lin-39 expression in the embryo, and hint at a

Dental Students' Educational Achievement in Relation to Their Learning Styles: A Cross-Sectional Study in Iran.

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Hosseini, Seyed Masoud; Amery, Hamideh; Emadzadeh, Ali; Babazadeh, Saber

2015-02-24

In recent decades, many studies have been carried out on the importance of Kolb experiential learning theory (ELT) in teaching-learning processes and its effect on learning outcomes. However, some experts have criticized the Kolb theory and argue that there are some ambiguities on the validity of the theory as an important predictor of achievement. This study has been carried out on dental students' educational achievement in relation to their dominant learning styles based on Kolb theory in Mashhad University of Medical Sciences (Iran). In a cross sectional study, Kolb Learning Style Inventory (LSI Ver. 3.1) as well as a questionnaire containing students' demographic data, academic achievement marks including grade point average (GPA), theoretical and practical courses marks, and the comprehensive basic sciences exam (CBSE) scores were administered on a purposive sample of 162 dental students who had passed their comprehensive basic sciences exam. Educational achievement data were analyzed in relation to students' dominant learning styles, using descriptive and analytical statistics including χ2, Kruskal-Wallis and two-way ANOVA tests. The dominant learning styles of students were Assimilating (53.1%), Converging (24.1%), Diverging (14.2%) and Accommodating (8.6%). Although, the students with Assimilating and Converging learning styles had a better performance on their educational achievement, there was no significant relationship between educational achievement and dominant learning style (P≥0.05). Findings support that the dominant learning style is not exclusively an essential factor to predict educational achievement. Rather, it shows learning preferences of students that may be considered in designing learning opportunities by the teachers.

Online Quiz Time Limits and Learning Outcomes in Economics

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Evans, Brent; Culp, Robert

2015-01-01

In an effort to better understand the impact of timing limits, the authors compare the learning outcomes of students who completed timed quizzes with students who took untimed quizzes in economics principles courses. Students were assigned two online quizzes--one timed and one untimed--and re-tested on the material the following class day. Our…

Forecasting air quality time series using deep learning.

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Freeman, Brian S; Taylor, Graham; Gharabaghi, Bahram; Thé, Jesse

2018-04-13

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O 3 ) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O 3 exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours. Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution

The time course of location-avoidance learning in fear of spiders.

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Rinck, Mike; Koene, Marieke; Telli, Sibel; Moerman-van den Brink, Wiltine; Verhoeven, Barbara; Becker, Eni S

2016-01-01

Two experiments were designed to study the time course of avoidance learning in spider fearfuls (SFs) under controlled experimental conditions. To achieve this, we employed an immersive virtual environment (IVE): While walking freely through a virtual art museum to search for specific paintings, the participants were exposed to virtual spiders. Unbeknown to the participants, only two of four museum rooms contained spiders, allowing for avoidance learning. Indeed, the more SF the participants were, the faster they learned to avoid the rooms that contained spiders (Experiment. 1), and within the first six trials, high fearfuls already developed a preference for starting their search task in rooms without spiders (Experiment 2). These results illustrate the time course of avoidance learning in SFs, and they speak to the usefulness of IVEs in fundamental anxiety research.

Influence of learning strategy on response time during complex value-based learning and choice.

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Shiva Farashahi

Full Text Available Measurements of response time (RT have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning. Alternatively, they could learn reward values of options' features (e.g. color, shape and combine these values to estimate reward values for individual options (feature-based learning. We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

The Negative Impact of Community Stressors on Learning Time: Examining Inequalities between California High Schools

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Mirra, Nicole; Rogers, John

2015-01-01

Allocated classroom time is not the same as time available for learning--a host of economic and social stressors undermine learning time in schools serving low-income students. When time is limited, it is hard to meet rigorous learning standards. The challenge is compounded in high-poverty schools where community stressors place additional demands…

Learning and Teaching Problems in Part-Time Higher Education.

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Trotman-Dickenson, D. I.

1988-01-01

Results of a British survey of the administrations of six universities and six public colleges, employers, and employees who were part-time students are reported and discussed. The survey assessed the perceptions of those groups concerning problems in the instruction and learning of part-time students. (MSE)

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

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Nicolas Frémaux

2013-04-01

Full Text Available Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD learning of Doya (2000 to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Fixation and escape times in stochastic game learning

International Nuclear Information System (INIS)

Realpe-Gomez, John; Szczesny, Bartosz; Galla, Tobias; Dall’Asta, Luca

2012-01-01

Evolutionary dynamics in finite populations is known to fixate eventually in the absence of mutation. We here show that a similar phenomenon can be found in stochastic game dynamical batch learning, and investigate fixation in learning processes in a simple 2×2 game, for two-player games with cyclic interaction, and in the context of the best-shot network game. The analogues of finite populations in evolution are here finite batches of observations between strategy updates. We study when and how such fixation can occur, and present results on the average time-to-fixation from numerical simulations. Simple cases are also amenable to analytical approaches and we provide estimates of the behaviour of so-called escape times as a function of the batch size. The differences and similarities with escape and fixation in evolutionary dynamics are discussed. (paper)

Students' Pressure, Time Management and Effective Learning

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Sun, Hechuan; Yang, Xiaolin

2009-01-01

Purpose: This paper aims to survey the status quo of the student pressure and the relationship between their daily time management and their learning outcomes in three different types of higher secondary schools at Shenyang, the capital city of Liaoning Province in mainland China. Design/methodology/approach: An investigation was carried out in 14…

Representation Learning from Time Labelled Heterogeneous Data for Mobile Crowdsensing

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Chunmei Ma

2016-01-01

Full Text Available Mobile crowdsensing is a new paradigm that can utilize pervasive smartphones to collect and analyze data to benefit users. However, sensory data gathered by smartphone usually involves different data types because of different granularity and multiple sensor sources. Besides, the data are also time labelled. The heterogeneous and time sequential data raise new challenges for data analyzing. Some existing solutions try to learn each type of data one by one and analyze them separately without considering time information. In addition, the traditional methods also have to determine phone orientation because some sensors equipped in smartphone are orientation related. In this paper, we think that a combination of multiple sensors can represent an invariant feature for a crowdsensing context. Therefore, we propose a new representation learning method of heterogeneous data with time labels to extract typical features using deep learning. We evaluate that our proposed method can adapt data generated by different orientations effectively. Furthermore, we test the performance of the proposed method by recognizing two group mobile activities, walking/cycling and driving/bus with smartphone sensors. It achieves precisions of 98.6% and 93.7% in distinguishing cycling from walking and bus from driving, respectively.

The race to learn: spike timing and STDP can coordinate learning and recall in CA3.

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Nolan, Christopher R; Wyeth, Gordon; Milford, Michael; Wiles, Janet

2011-06-01

The CA3 region of the hippocampus has long been proposed as an autoassociative network performing pattern completion on known inputs. The dentate gyrus (DG) region is often proposed as a network performing the complementary function of pattern separation. Neural models of pattern completion and separation generally designate explicit learning phases to encode new information and assume an ideal fixed threshold at which to stop learning new patterns and begin recalling known patterns. Memory systems are significantly more complex in practice, with the degree of memory recall depending on context-specific goals. Here, we present our spike-timing separation and completion (STSC) model of the entorhinal cortex (EC), DG, and CA3 network, ascribing to each region a role similar to that in existing models but adding a temporal dimension by using a spiking neural network. Simulation results demonstrate that (a) spike-timing dependent plasticity in the EC-CA3 synapses provides a pattern completion ability without recurrent CA3 connections, (b) the race between activation of CA3 cells via EC-CA3 synapses and activation of the same cells via DG-CA3 synapses distinguishes novel from known inputs, and (c) modulation of the EC-CA3 synapses adjusts the learned versus test input similarity required to evoke a direct CA3 response prior to any DG activity, thereby adjusting the pattern completion threshold. These mechanisms suggest that spike timing can arbitrate between learning and recall based on the novelty of each individual input, ensuring control of the learn-recall decision resides in the same subsystem as the learned memories themselves. The proposed modulatory signal does not override this decision but biases the system toward either learning or recall. The model provides an explanation for empirical observations that a reduction in novelty produces a corresponding reduction in the latency of responses in CA3 and CA1. Copyright © 2010 Wiley-Liss, Inc.

Pointillist, Cyclical, and Overlapping: Multidimensional Facets of Time in Online Learning

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Pekka Ihanainen

2011-11-01

Full Text Available A linear, sequential time conception based on in-person meetings and pedagogical activities is not enough for those who practice and hope to enhance contemporary education, particularly where online interactions are concerned. In this article, we propose a new model for understanding time in pedagogical contexts. Conceptual parts of the model will be employed as a “cultural technology” to help us relate to evolving phenomena, both physical and virtual. We label these constructs as pointillist, cyclical, and overlapping times.Pointillist time and learning takes place in “dots” of actions that consist of small, discrete moments (e.g., tweeting. Producing, receiving, and sharing ideas in this context are separate points in each actor’s timeline. Cyclical time and learning emerges from intensive periods, which are highly visible in online forums. This construct reveals itself through interactions that often exist in multiple online environments. Overlapping time and learning involves various configurations of linear, pointillist, and cyclical layers, which are mainly evident through the simultaneous uses of social communication technologies.Pointillist, cyclical, and overlapping time constructs enable new orientations for conceptualizing time in pedagogy. In this article we also introduce de-, re-, and en- modes of these pedagogies that connect with approaches to meet the needs of learners for individualization, personalization, and cyborgization.

Identification of critical time-consuming student support activities in e-learning

NARCIS (Netherlands)

De Vries, Fred; Kester, Liesbeth; Sloep, Peter; Van Rosmalen, Peter; Pannekeet, Kees; Koper, Rob

2005-01-01

Please cite the original publication: De Vries, F., Kester, L., Sloep, P., Van Rosmalen, P., Pannekeet, K., & Koper, R. (2005). Identification of critical time-consuming student support activities in e-learning. Research in Learning Technology (ALT-J), 13(3), 219-229.

Autonomous learning by simple dynamical systems with a discrete-time formulation

Science.gov (United States)

Bilen, Agustín M.; Kaluza, Pablo

2017-05-01

We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.

Prime Time for Learning.

Science.gov (United States)

Leidy, Vivian; And Others

1981-01-01

Five elementary teachers explain how they orient pupils and get learning started on the first day of school--whether or not their supplies or textbooks have arrived--by building learning activities around a common interest like dogs, earthworms, football, or the Statue of Liberty. (Editor/SJL)

Capitalizing on Speaking Skill of EFL Learners for the Language Literacy

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Fauzia Hasan Siddiqui

2014-03-01

Full Text Available This study aims at grabbing the attention of EFL /ESL teachers, trainers, and administrators towards the importance of teaching speaking skill to enhance overall language proficiency of EFL learners. Comprehensive research done in the field of applied linguistics and English Language Teaching (ELT establishes a positive correlation of speaking skill with the overall language proficiency. Despite this obvious significance of speaking skill in language learning process, it has not gained sufficient attention in the ELT or the assessments in Oman.  Relying on the available literature on the importance of the speaking skill and its effective role in enhancing other language macro skills (listening, reading, and writing, this exploratory research analyzes the currents status of speaking skill in ELT and assessments at the General Foundation Programme (GFP in Oman. As many GFP’s have IELTS (International English Language Testing System  exam as their programme exit examination, the study begins with measuring the correlation of speaking skill grades with other macro skill in order to accentuate the positive impact of speaking skill on other language skills. Secondly, it presents the statistics of time devoted to teaching and weights that speaking skill hold in the GFP in Oman. Finally, the study suggests the ways to optimize speaking skill opportunities to create successful literacy experience among adult EFL learners.

Event timing in associative learning: from biochemical reaction dynamics to behavioural observations.

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Ayse Yarali

Full Text Available Associative learning relies on event timing. Fruit flies for example, once trained with an odour that precedes electric shock, subsequently avoid this odour (punishment learning; if, on the other hand the odour follows the shock during training, it is approached later on (relief learning. During training, an odour-induced Ca(++ signal and a shock-induced dopaminergic signal converge in the Kenyon cells, synergistically activating a Ca(++-calmodulin-sensitive adenylate cyclase, which likely leads to the synaptic plasticity underlying the conditioned avoidance of the odour. In Aplysia, the effect of serotonin on the corresponding adenylate cyclase is bi-directionally modulated by Ca(++, depending on the relative timing of the two inputs. Using a computational approach, we quantitatively explore this biochemical property of the adenylate cyclase and show that it can generate the effect of event timing on associative learning. We overcome the shortage of behavioural data in Aplysia and biochemical data in Drosophila by combining findings from both systems.

Optimal critic learning for robot control in time-varying environments.

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Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Timing of quizzes during learning: Effects on motivation and retention.

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Healy, Alice F; Jones, Matt; Lalchandani, Lakshmi A; Tack, Lindsay Anderson

2017-06-01

This article investigates how the timing of quizzes given during learning impacts retention of studied material. We investigated the hypothesis that interspersing quizzes among study blocks increases student engagement, thus improving learning. Participants learned 8 artificial facts about each of 8 plant categories, with the categories blocked during learning. Quizzes about 4 of the 8 facts from each category occurred either immediately after studying the facts for that category (standard) or after studying the facts from all 8 categories (postponed). In Experiment 1, participants were given tests shortly after learning and several days later, including both the initially quizzed and unquizzed facts. Test performance was better in the standard than in the postponed condition, especially for categories learned later in the sequence. This result held even for the facts not quizzed during learning, suggesting that the advantage cannot be due to any direct testing effects. Instead the results support the hypothesis that interrupting learning with quiz questions is beneficial because it can enhance learner engagement. Experiment 2 provided further support for this hypothesis, based on participants' retrospective ratings of their task engagement during the learning phase. These findings have practical implications for when to introduce quizzes in the classroom. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Flexible Learning and Teaching: Looking Beyond the Binary of Full-time/Part-time Provision in South African Higher Education

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Barbara M Jones

2015-06-01

Full Text Available This paper engages with literature on flexible learning and teaching in order to explore whether it may be possible, within the South African context, to have flexible learning and teaching provide a third way which goes beyond the current practice of full-time/part-time provision. This binary classification of students is a proxy for day-time/after-hours delivery.  The argument is made that effective, flexible learning and teaching requires a fundamental shift in thinking about learning and teaching in higher education that moves us beyond such binaries. The paper proposes that in order to ensure access and success for students, ‘common knowledge’ (Edwards, 2010 will need to be co-constructed which understands flexible learning and teaching in ways which will meet needs of a diversity of students, including working students. It will require ‘resourceful leadership’ (Edwards, 2014 within the university that recognises, enhances and gives purpose to the capability of colleagues at every level of the systems they lead. Also, it will require the building of ‘common knowledge’ between certain sectors of universities and particular workplaces.

Editorial

OpenAIRE

Koksal, Dincay

2013-01-01

Dear ELT Research Journal Reader,We are pleased to publish the third issue of ELT Research Journal that covers varioustopics in the field of ELT. As we have been receiving great support from our interestedauthors, we would like to extend our appreciation to those who consider our journal to submittheir works. Moreover, we would also like to thank to our reviewers who have been devotingtheir time.In this third issue of the first volume, we have four research articles in addition to twobook rev...

Dental Students’ Educational Achievement in Relation to Their Learning Styles: A Cross-sectional Study in Iran

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Hosseini, Seyed Masoud; Amery, Hamideh; Emadzadeh, Ali; Babazadeh, Saber

2015-01-01

Background and Objectives: In recent decades, many studies have been carried out on the importance of Kolb experiential learning theory (ELT) in teaching-learning processes and its effect on learning outcomes. However, some experts have criticized the Kolb theory and argue that there are some ambiguities on the validity of the theory as an important predictor of achievement. This study has been carried out on dental students’ educational achievement in relation to their dominant learning styles based on Kolb theory in Mashhad University of Medical Sciences (Iran). Methods: In a cross sectional study, Kolb Learning Style Inventory (LSI Ver. 3.1) as well as a questionnaire containing students’ demographic data, academic achievement marks including grade point average (GPA), theoretical and practical courses marks, and the comprehensive basic sciences exam (CBSE) scores were administered on a purposive sample of 162 dental students who had passed their comprehensive basic sciences exam. Educational achievement data were analyzed in relation to students’ dominant learning styles, using descriptive and analytical statistics including χ2, Kruskal-Wallis and two-way ANOVA tests. Results: The dominant learning styles of students were Assimilating (53.1%), Converging (24.1%), Diverging (14.2%) and Accommodating (8.6%). Although, the students with Assimilating and Converging learning styles had a better performance on their educational achievement, there was no significant relationship between educational achievement and dominant learning style (P≥0.05). Conclusion: Findings support that the dominant learning style is not exclusively an essential factor to predict educational achievement. Rather, it shows learning preferences of students that may be considered in designing learning opportunities by the teachers. PMID:26156915

In-Time On-Place Learning

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Bauters, Merja; Purma, Jukka; Leinonen, Teemu

2014-01-01

The aim of this short paper is to look at how mobile video recording devices could support learning related to physical practices or places and situations at work. This paper discusses particular kind of workplace learning, namely learning using short video clips that are related to physical environment and tasks preformed in situ. The paper…

EFFECTS OF COOPERATIVE LEARNING MODEL TYPE STAD JUST-IN TIME BASED ON THE RESULTS OF LEARNING TEACHING PHYSICS COURSE IN PHYSICS SCHOOL IN PHYSICS PROGRAM FACULTY UNIMED

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Teguh Febri Sudarma

2013-06-01

Full Text Available Research was aimed to determine: (1 Students’ learning outcomes that was taught with just in time teaching based STAD cooperative learning method and STAD cooperative learning method (2 Students’ outcomes on Physics subject that had high learning activity compared with low learning activity. The research sample was random by raffling four classes to get two classes. The first class taught with just in time teaching based STAD cooperative learning method, while the second class was taught with STAD cooperative learning method. The instrument used was conceptual understanding that had been validated with 7 essay questions. The average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,47 higher than average gain values of students learning results with STAD cooperative learning method. The high learning activity and low learning activity gave different learning results. In this case the average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,48 higher than average gain values of students learning results with STAD cooperative learning method. There was interaction between learning model and learning activity to the physics learning result test in students

Investigating the Relationship Between Self-Directed Learning Readiness and Time Management Skills in Turkish Undergraduate Nursing Students.

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Ertuğ, Nurcan; Faydali, Saide

The aims of this study were to determine self-directed learning and time management skills of undergraduate nursing students and to investigate the relationship between the concepts. The use of self-directed learning has increased as an educational strategy in recent years. This descriptive and correlational study was conducted with 383 undergraduate nursing students in Turkey. Data were collected using a sociodemographic questionnaire, the Self-Directed Learning Readiness Scale, and Time Management Questionnaire. Mean scores were as follows: self-directed learning readiness, 159.12 (SD = 20.8); time management, 87.75 (SD = 12.1). A moderate positive correlation was found between self-directed learning readiness and time management values. Time management scores were 78.42 when self-directed learning readiness was ≤149 and 90.82 when self-directed learning readiness was ≥ 150, with a statistically significant difference (p = .000). Level of self-directed learning and academic achievement were higher in students who managed their time well.

Children benefit differently from night- and day-time sleep in motor learning.

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Yan, Jin H

2017-08-01

Motor skill acquisition occurs while practicing (on-line) and when asleep or awake (off-line). However, developmental questions still remain about whether children of various ages benefit similarly or differentially from night- and day-time sleeping. The likely circadian effects (time-of-day) and the possible between-test-interference (order effects) associated with children's off-line motor learning are currently unknown. Therefore, this study examines the contributions of over-night sleeping and mid-day napping to procedural skill learning. One hundred and eight children were instructed to practice a finger sequence task using computer keyboards. After an equivalent 11-h interval in one of the three states (sleep, nap, wakefulness), children performed the same sequence in retention tests and a novel sequence in transfer tests. Changes in the movement time and sequence accuracy were evaluated between ages (6-7, 8-9, 10-11years) during practice, and from skill training to retrievals across three states. Results suggest that night-time sleeping and day-time napping improved the tapping speed, especially for the 6-year-olds. The circadian factor did not affect off-line motor learning in children. The interference between the two counter-balanced retrieval tests was not found for the off-line motor learning. This research offers possible evidence about the age-related motor learning characteristics in children and a potential means for enhancing developmental motor skills. The dynamics between age, experience, memory formation, and the theoretical implications of motor skill acquisition are discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Polysynchronous: Dialogic Construction of Time in Online Learning

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Oztok, Murat; Wilton, Lesley; Zingaro, Daniel; Mackinnon, Kim; Makos, Alexandra; Phirangee, Krystle; Brett, Clare; Hewitt, Jim

2014-01-01

Online learning has been conceptualized for decades as being delivered in one of two modes: synchronous or asynchronous. Technological determinism falls short in describing the role that the individuals' psychological, social and pedagogical factors play in their perception, experience and understanding of time online. This article explores…

Online gaming for learning optimal team strategies in real time

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Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

2010-04-01

This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

Effects of Business School Student's Study Time on the Learning Process

Science.gov (United States)

Tetteh, Godson Ayertei

2016-01-01

Purpose: This paper aims to clarify the relationship between the student's study time and the learning process in the higher education system by adapting the total quality management (TQM) principles-process approach. Contrary to Deming's (1982) constancy of purpose to improve the learning process, some students in higher education postpone their…

Finite time convergent learning law for continuous neural networks.

Science.gov (United States)

Chairez, Isaac

2014-02-01

This paper addresses the design of a discontinuous finite time convergent learning law for neural networks with continuous dynamics. The neural network was used here to obtain a non-parametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties was the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on discontinuous algorithms was used to adjust the weights of the neural network. The adaptive algorithm was derived by means of a non-standard Lyapunov function that is lower semi-continuous and differentiable in almost the whole space. A compensator term was included in the identifier to reject some specific perturbations using a nonlinear robust algorithm. Two numerical examples demonstrated the improvements achieved by the learning algorithm introduced in this paper compared to classical schemes with continuous learning methods. The first one dealt with a benchmark problem used in the paper to explain how the discontinuous learning law works. The second one used the methane production model to show the benefits in engineering applications of the learning law proposed in this paper. Copyright © 2013 Elsevier Ltd. All rights reserved.

INDIRECT WRITTEN CORRECTIVE FEEDBACK, REVISION, AND LEARNING

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Fatemeh Poorebrahim

2017-01-01

Full Text Available Corrective feedback, the necessity of providing it, and how it should be provided has been one of the hot topics in the area of ELT. Amid continuing controversies over whether providing feedback helps L2 learners improve their writing accuracy, many research studies have been undertaken to compare the relative effectiveness of different types of feedback. However, the difference between two types of indirect corrective feedback, namely indication and indication plus location, have not been properly examined yet. Motivated to narrow this gap, this study is designed to compare two groups of Iranian learners, each revising their papers based on one of the aforementioned options. For data analysis, a series of independent samples t tests were employed. The results revealed that the difference between the two groups in their reduction of errors from the original draft to the revision of each task followed a growing trend and became significant. Nonetheless, the difference in accuracy of new pieces of writing fell short of significance. Finally, it was found that error reduction in revision stage cannot be considered as learning. The results of the study, discussed in relation to that of others, implicate that the purpose for which feedback is provided is essential in determining the type of feedback; more explicit feedback is better for revising purposes while more implicit feedback is good for learning purposes.

TEXPLORE temporal difference reinforcement learning for robots and time-constrained domains

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Hester, Todd

2013-01-01

This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time. Robots have the potential to solve many problems in society, because of their ability to work in dangerous places doing necessary jobs that no one wants or is able to do. One barrier to their widespread deployment is that they are mainly limited to tasks where it is possible to hand-program behaviors for every situation that may be encountered. For robots to meet their potential, they need methods that enable them to learn and adapt to novel situations that they were not programmed for. Reinforcement learning (RL) is a paradigm for learning sequential decision making processes and could solve the problems of learning and adaptation on robots. This book identifies four key challenges that must be addressed for an RL algorithm to be practical for robotic control tasks. These RL for Robotics Challenges are: 1) it must learn in very few samples; 2) it must learn in domains with continuou...

Problem based learning: the effect of real time data on the website to student independence

Science.gov (United States)

Setyowidodo, I.; Pramesti, Y. S.; Handayani, A. D.

2018-05-01

Learning science developed as an integrative science rather than disciplinary education, the reality of the nation character development has not been able to form a more creative and independent Indonesian man. Problem Based Learning based on real time data in the website is a learning method focuses on developing high-level thinking skills in problem-oriented situations by integrating technology in learning. The essence of this study is the presentation of authentic problems in the real time data situation in the website. The purpose of this research is to develop student independence through Problem Based Learning based on real time data in website. The type of this research is development research with implementation using purposive sampling technique. Based on the study there is an increase in student self-reliance, where the students in very high category is 47% and in the high category is 53%. This learning method can be said to be effective in improving students learning independence in problem-oriented situations.

Touchscreen Facilitates Young Children’s Transfer of Learning to Tell Time

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Fuxing Wang

2016-11-01

Full Text Available Young children are devoting increasing time to playing on handheld touchscreen devices (e.g., iPads. Though thousands of touchscreen apps are claimed to be educational, there is a lack of sufficient evidence examining the impact of touchscreens on children’s learning outcomes. In the present study, the two questions we focused on were (a whether using a touchscreen was helpful in teaching children to tell time, and (b to what extent young children could transfer what they had learned on the touchscreen to other media. A pre- and posttest design was adopted. After learning to read the time on the iPad touchscreen for 10 minutes, three groups of 5- to 6-year-old children (N = 65 were respectively tested with an iPad touchscreen, a toy clock or a drawing of a clock on paper. The results revealed that posttest scores in the iPad touchscreen test group were significantly higher than those at pretest, indicating that the touchscreen itself could provide support for young children’s learning. Similarly, regardless of being tested with a toy clock or paper drawing, children’s posttest performance was also better than pretest, suggesting that children could transfer what they had learned on an iPad touchscreen to other media. However, comparison among groups showed that children tested with the paper drawing underperformed those tested with the other two media. The theoretical and practical implications of the results, as well as limitations of the present study, are discussed.

Sensitivity analysis of machine-learning models of hydrologic time series

Science.gov (United States)

O'Reilly, A. M.

2017-12-01

Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

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Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

Operational Differences Between MEOSAR and GEO/LEOSAR Capabilities

Science.gov (United States)

2009-02-01

deviendra opérationnel. DRDC CORA TM 2009-011 ix Les principales constatations faites par les auteurs du présent rapport sont énumérées dans...In theory , lives would also be saved with properly working ELTs since it reduces search time by about 45 hours. Recommendation: ELTs

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

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Joseph, A; Herrera, D; Hijal, T; Kildea, J; Hendren, L; Leung, A; Wainberg, J; Sawaf, M; Gorshkov, M; Maglieri, R; Keshavarz, M

2016-01-01

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Joseph, A; Herrera, D; Hijal, T; Kildea, J [McGill University Health Centre, Montreal, Quebec (Canada); Hendren, L; Leung, A; Wainberg, J; Sawaf, M; Gorshkov, M; Maglieri, R; Keshavarz, M [McGill University, Montreal, Quebec (Canada)

2016-06-15

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes

Incremental Impact of Time on Students' Use of E-Learning via Facebook

Science.gov (United States)

Moghavvemi, Sedigheh; Salarzadeh Janatabadi, Hashem

2018-01-01

The majority of studies utilised the cross-sectional method to measure students' intention to learn and investigate their corresponding learning behaviours. Only a few studies have measured the process of change in students' learning behaviour in the context of time. The main purpose of this study is to determine the effects of using a Facebook…

Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples

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Mingchen Yao

2015-01-01

Full Text Available Many generalization results in learning theory are established under the assumption that samples are independent and identically distributed (i.i.d.. However, numerous learning tasks in practical applications involve the time-dependent data. In this paper, we propose a theoretical framework to analyze the generalization performance of the empirical risk minimization (ERM principle for sequences of time-dependent samples (TDS. In particular, we first present the generalization bound of ERM principle for TDS. By introducing some auxiliary quantities, we also give a further analysis of the generalization properties and the asymptotical behaviors of ERM principle for TDS.

Making time for learning-oriented leadership in multidisciplinary hospital management groups.

Science.gov (United States)

Singer, Sara J; Hayes, Jennifer E; Gray, Garry C; Kiang, Mathew V

2015-01-01

Although the clinical requirements of health care delivery imply the need for interdisciplinary management teams to work together to promote frontline learning, such interdisciplinary, learning-oriented leadership is atypical. We designed this study to identify behaviors enabling groups of diverse managers to perform as learning-oriented leadership teams on behalf of quality and safety. We randomly selected 12 of 24 intact groups of hospital managers from one hospital to participate in a Safety Leadership Team Training program. We collected primary data from March 2008 to February 2010 including pre- and post-staff surveys, multiple interviews, observations, and archival data from management groups. We examined the level and trend in frontline perceptions of managers' learning-oriented leadership following the intervention and ability of management groups to achieve objectives on targeted improvement projects. Among the 12 intervention groups, we identified higher- and lower-performing intervention groups and behaviors that enabled higher performers to work together more successfully. Management groups that achieved more of their performance goals and whose staff perceived more and greater improvement in their learning-oriented leadership after participation in Safety Leadership Team Training invested in structures that created learning capacity and conscientiously practiced prescribed learning-oriented management and problem-solving behaviors. They made the time to do these things because they envisioned the benefits of learning, valued the opportunity to learn, and maintained an environment of mutual respect and psychological safety within their group. Learning in management groups requires vision of what learning can accomplish; will to explore, practice, and build learning capacity; and mutual respect that sustains a learning environment.

Active controllers and the time duration to learn a task

Science.gov (United States)

Repperger, D. W.; Goodyear, C.

1986-01-01

An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

Crumpled Molecules and Edible Plastic: Science Learning Activation in Out-of-School Time

Science.gov (United States)

Dorph, Rena; Schunn, Christian D.; Crowley, Kevin

2017-01-01

The Coalition for Science After School highlights the dual nature of outcomes for science learning during out-of- school time (OST): Learning experiences should not only be positive in the moment, but also position youth for future success. Several frameworks speak to the first set of immediate outcomes--what youth learn, think, and feel as the…

Oscillations, Timing, Plasticity, and Learning in the Cerebellum.

Science.gov (United States)

Cheron, G; Márquez-Ruiz, J; Dan, B

2016-04-01

The highly stereotyped, crystal-like architecture of the cerebellum has long served as a basis for hypotheses with regard to the function(s) that it subserves. Historically, most clinical observations and experimental work have focused on the involvement of the cerebellum in motor control, with particular emphasis on coordination and learning. Two main models have been suggested to account for cerebellar functioning. According to Llinás's theory, the cerebellum acts as a control machine that uses the rhythmic activity of the inferior olive to synchronize Purkinje cell populations for fine-tuning of coordination. In contrast, the Ito-Marr-Albus theory views the cerebellum as a motor learning machine that heuristically refines synaptic weights of the Purkinje cell based on error signals coming from the inferior olive. Here, we review the role of timing of neuronal events, oscillatory behavior, and synaptic and non-synaptic influences in functional plasticity that can be recorded in awake animals in various physiological and pathological models in a perspective that also includes non-motor aspects of cerebellar function. We discuss organizational levels from genes through intracellular signaling, synaptic network to system and behavior, as well as processes from signal production and processing to memory, delegation, and actual learning. We suggest an integrative concept for control and learning based on articulated oscillation templates.

Associations between Salivary Testosterone Levels, Androgen‐Related Genetic Polymorphisms, and Self‐Estimated Ejaculation Latency Time

Directory of Open Access Journals (Sweden)

Patrick Jern, PhD

2014-08-01

Conclusions: We were unable to find support for the hypothesis suggesting an association between T levels and ELT, possibly because of the low number of phenotypically extreme cases (the sample used in the present study was population based. Our results concerning genetic associations should be interpreted with caution until replication studies have been conducted. Jern P, Westberg L, Ankarberg‐Lindgren C, Johansson A, Gunst A, Sandnabba NK, and Santtila P. Associations between salivary testosterone levels, androgen‐related genetic polymorphisms, and self‐estimated ejaculation latency time. Sex Med 2014;2:107–114.

Autism: Too eager to learn? Event related potential findings of increased dependency on intentional learning in a serial reaction time task.

Science.gov (United States)

Zwart, Fenny S; Vissers, Constance Th W M; van der Meij, Roemer; Kessels, Roy P C; Maes, Joseph H R

2017-09-01

It has been suggested that people with autism spectrum disorder (ASD) have an increased tendency to use explicit (or intentional) learning strategies. This altered learning may play a role in the development of the social communication difficulties characterizing ASD. In the current study, we investigated incidental and intentional sequence learning using a Serial Reaction Time (SRT) task in an adult ASD population. Response times and event related potentials (ERP) components (N2b and P3) were assessed as indicators of learning and knowledge. Findings showed that behaviorally, sequence learning and ensuing explicit knowledge were similar in ASD and typically developing (TD) controls. However, ERP findings showed that learning in the TD group was characterized by an enhanced N2b, while learning in the ASD group was characterized by an enhanced P3. These findings suggest that learning in the TD group might be more incidental in nature, whereas learning in the ASD group is more intentional or effortful. Increased intentional learning might serve as a strategy for individuals with ASD to control an overwhelming environment. Although this led to similar behavioral performances on the SRT task, it is very plausible that this intentional learning has adverse effects in more complex social situations, and hence contributes to the social impairments found in ASD. Autism Res 2017, 10: 1533-1543. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

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Christian Albers

Full Text Available Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP. Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious and strong (teacher spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

Science.gov (United States)

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Cluster analysis of activity-time series in motor learning

DEFF Research Database (Denmark)

Balslev, Daniela; Nielsen, Finn Å; Futiger, Sally A

2002-01-01

Neuroimaging studies of learning focus on brain areas where the activity changes as a function of time. To circumvent the difficult problem of model selection, we used a data-driven analytic tool, cluster analysis, which extracts representative temporal and spatial patterns from the voxel......-time series. The optimal number of clusters was chosen using a cross-validated likelihood method, which highlights the clustering pattern that generalizes best over the subjects. Data were acquired with PET at different time points during practice of a visuomotor task. The results from cluster analysis show...

Learning to stay ahead of time

DEFF Research Database (Denmark)

Staunæs, Dorthe; Raffnsøe, Sverre

2014-01-01

In the context of an ongoing change, management is required to take the form of a leadership that must be reignited over and over again. The article examines a new art of leadership that may be viewed as an attempt to keep up with these challenges and stay ahead of time. It emerges from...... a pilgrimage leadership learning laboratory on the road to Santiago de la Compostela. This moving lab creates situations of extraordinary intensity that border on hyperreality and force the leader to find him/herself anew on the verge of him/herself. Conceived as pilgrimage, leadership moves ahead of time...... as it reaches into and anticipates a future still unknown. In this setting, anticipatory affects and the virtual take up a predominant role. As it emerges here, leadership distinguishes itself not only from leadership in the traditional sense, but also from management and governmentality....

Graded Proteasome Dysfunction in Caenorhabditis elegans Activates an Adaptive Response Involving the Conserved SKN-1 and ELT-2 Transcription Factors and the Autophagy-Lysosome Pathway.

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Scott A Keith

2016-02-01

Full Text Available The maintenance of cellular proteins in a biologically active and structurally stable state is a vital endeavor involving multiple cellular pathways. One such pathway is the ubiquitin-proteasome system that represents a major route for protein degradation, and reductions in this pathway usually have adverse effects on the health of cells and tissues. Here, we demonstrate that loss-of-function mutants of the Caenorhabditis elegans proteasome subunit, RPN-10, exhibit moderate proteasome dysfunction and unexpectedly develop both increased longevity and enhanced resistance to multiple threats to the proteome, including heat, oxidative stress, and the presence of aggregation prone proteins. The rpn-10 mutant animals survive through the activation of compensatory mechanisms regulated by the conserved SKN-1/Nrf2 and ELT-2/GATA transcription factors that mediate the increased expression of genes encoding proteasome subunits as well as those mediating oxidative- and heat-stress responses. Additionally, we find that the rpn-10 mutant also shows enhanced activity of the autophagy-lysosome pathway as evidenced by increased expression of the multiple autophagy genes including atg-16.2, lgg-1, and bec-1, and also by an increase in GFP::LGG-1 puncta. Consistent with a critical role for this pathway, the enhanced resistance of the rpn-10 mutant to aggregation prone proteins depends on autophagy genes atg-13, atg-16.2, and prmt-1. Furthermore, the rpn-10 mutant is particularly sensitive to the inhibition of lysosome activity via either RNAi or chemical means. We also find that the rpn-10 mutant shows a reduction in the numbers of intestinal lysosomes, and that the elt-2 gene also plays a novel and vital role in controlling the production of functional lysosomes by the intestine. Overall, these experiments suggest that moderate proteasome dysfunction could be leveraged to improve protein homeostasis and organismal health and longevity, and that the rpn-10 mutant

Enhancement of Online Robotics Learning Using Real-Time 3D Visualization Technology

OpenAIRE

Richard Chiou; Yongjin (james) Kwon; Tzu-Liang (bill) Tseng; Robin Kizirian; Yueh-Ting Yang

2010-01-01

This paper discusses a real-time e-Lab Learning system based on the integration of 3D visualization technology with a remote robotic laboratory. With the emergence and development of the Internet field, online learning is proving to play a significant role in the upcoming era. In an effort to enhance Internet-based learning of robotics and keep up with the rapid progression of technology, a 3- Dimensional scheme of viewing the robotic laboratory has been introduced in addition to the remote c...

Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

Science.gov (United States)

Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

2014-01-01

The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P < .01) and learning adaptability (F = 4.41, P < .01) differed across grade groups. Learning adaptability (r = 0.382, P < .01) and time management disposition (r = 0.741, P < .01) were positively related with study engagement. Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management. Copyright © 2014 Elsevier Inc. All rights reserved.

[A technological device for optimizing the time taken for blind people to learn Braille].

Science.gov (United States)

Hernández, Cesar; Pedraza, Luis F; López, Danilo

2011-10-01

This project was aimed at designing and putting an electronic prototype into practice for improving the initial time taken by visually handicapped people for learning Braille, especially children. This project was mainly based on a prototype digital electronic device which identifies and translates material written by a user in Braille by a voice synthesis system, producing artificial words to determine whether a handicapped person's writing in Braille has been correct. A global system for mobile communications (GSM) module was also incorporated into the device which allowed it to send text messages, thereby involving innovation in the field of articles for aiding visually handicapped people. This project's main result was an easily accessed and understandable prototype device which improved visually handicapped people's initial learning of Braille. The time taken for visually handicapped people to learn Braille became significantly reduced whilst their interest increased, as did their concentration time regarding such learning.

INQUIRY –BASED LEARNING FOR ENHANCING CRITICAL THINKING SKILLS: INDONESIAN STUDENTS‘ PERSPECTIVES

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Hersulastuti Hersulastuti

2017-12-01

Full Text Available This paper was mainly intended to shed light on students‘ response towards the implementation of Inquiry-Based Learning (IBL in Reading and Writing subject, and explore its benefits for enhancing critical thinking skills from students‘perspectives in ELT context. This research was conducted through a qualitative case study approach. Three students of graduate program were purposively selected to be the participants. Data were gathered primarily from observation notes and interviews, and then further analyzed using interractive model analysis as proposed by Miles & Huberman (1994. The findings demonstrate that students have good responses towards the implementation of IBL. Moreover, IBL is beneficial to make students become more self-directed, selfdisciplined, self-monitored thinkers. Through IBL, students develop their critical thinking abilities: 1 raise vital questions and problems; 2 gather and assess relevant information; 3 drawing well-reasoned conclusions; and 4 communicate effectively with others to seek solution to complex problems.

Evaluating Speech acts in ELT Textbooks: The Case of Compliments and Complaints in the Touchstone Series

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Mahdieh Jalilian

2016-07-01

Full Text Available Textbooks play an important role in English Language Teaching (ELT, particularly in the English as a Foreign Language (EFL context where it provides the primary linguistic input. The present research was an attempt to comparatively evaluate the Touchstone series in terms of compliment and complaint speech acts. Four Touchstone textbooks (Book 1, Book 2, Book 3, and Book 4 were selected and content analysis was done using Olshtain and Weinbach’s (1993 complaint strategies and Wolfson and Manes’ (1980 classification of compliment. The frequencies and percentages of compliments and complaint speech acts were obtained. Data analysis showed that, first, the total frequency of the complaint speech act was higher in Touchstone, Book 4 than the other three textbooks; second, the frequency of complaint and compliment speech acts in the Writing section was quite low, but the Conversation section had a high frequency of compliment speech act in the Touchstone series; third, the expression of annoyance or disapproval complaint strategy was frequently used in the Touchstone series; fourth, the compliment strategy of ‘noun phrase + looks/is (intensifier adjective’ was very frequent in the Touchstone series; finally, there was a significant difference between the frequencies of the two speech acts, in general, in the four Touchstone textbooks. Considering the weaknesses and strengthens of Touchstone series, implications for teachers, material developers, and textbook writers are provided.

Time-sensitive Customer Churn Prediction based on PU Learning

OpenAIRE

Wang, Li; Chen, Chaochao; Zhou, Jun; Li, Xiaolong

2018-01-01

With the fast development of Internet companies throughout the world, customer churn has become a serious concern. To better help the companies retain their customers, it is important to build a customer churn prediction model to identify the customers who are most likely to churn ahead of time. In this paper, we propose a Time-sensitive Customer Churn Prediction (TCCP) framework based on Positive and Unlabeled (PU) learning technique. Specifically, we obtain the recent data by shortening the...

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

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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.

Influencing Work-Related Learning: The Role of Job Characteristics and Self-Directed Learning Orientation in Part-Time Vocational Education

Science.gov (United States)

Gijbels, David; Raemdonck, Isabel; Vervecken, Dries

2010-01-01

Based on the Demand-Control-Support (DCS) model, the present paper aims to investigate the influence of job characteristics such as job demands, job control, social support at work and self-directed learning orientation on the work-related learning behaviour of workers. The present study was conducted in a centre for part-time vocational education…

Probability Learning: Changes in Behavior across Time and Development

Science.gov (United States)

Plate, Rista C.; Fulvio, Jacqueline M.; Shutts, Kristin; Green, C. Shawn; Pollak, Seth D.

2018-01-01

Individuals track probabilities, such as associations between events in their environments, but less is known about the degree to which experience--within a learning session and over development--influences people's use of incoming probabilistic information to guide behavior in real time. In two experiments, children (4-11 years) and adults…

Learning of temporal motor patterns: An analysis of continuous vs. reset timing

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Rodrigo eLaje

2011-10-01

Full Text Available Our ability to generate well-timed sequences of movements is critical to an array of behaviors, including the ability to play a musical instrument or a video game. Here we address two questions relating to timing with the goal of better understanding the neural mechanisms underlying temporal processing. First, how does accuracy and variance change over the course of learning of complex spatiotemporal patterns? Second, is the timing of sequential responses most consistent with starting and stopping an internal timer at each interval or with continuous timing?To address these questions we used a psychophysical task in which subjects learned to reproduce a sequence of finger taps in the correct order and at the correct times—much like playing a melody at the piano. This task allowed us to calculate the variance of the responses at different time points using data from the same trials. Our results show that while standard Weber’s law is clearly violated, variance does increase as a function of time squared, as expected according to the generalized form of Weber’s law—which separates the source of variance into time-dependent and time-independent components. Over the course of learning, both the time-independent variance and the coefficient of the time-dependent term decrease. Our analyses also suggest that timing of sequential events does not rely on the resetting of an internal timer at each event.We describe and interpret our results in the context of computer simulations that capture some of our psychophysical findings. Specifically, we show that continuous timing, as opposed to reset timing, is expected from population clock models in which timing emerges from the internal dynamics of recurrent neural networks.

A Distance Learning Review--The Communicational Module "Learning on Demand--Anywhere at Any Time"

Science.gov (United States)

Tatkovic, Nevenka; Ruzic, Maja

2004-01-01

The society of knowledge refers to the society marked with the principle which requires that knowledge, information and life-time learning hold a key to success in the world of IT technology. Internet, World Wide Web, Web Based Education and ever so growing speed of IT and communicational technologies have enabled the application of new modes,…

Overlay improvements using a real time machine learning algorithm

Science.gov (United States)

Schmitt-Weaver, Emil; Kubis, Michael; Henke, Wolfgang; Slotboom, Daan; Hoogenboom, Tom; Mulkens, Jan; Coogans, Martyn; ten Berge, Peter; Verkleij, Dick; van de Mast, Frank

2014-04-01

While semiconductor manufacturing is moving towards the 14nm node using immersion lithography, the overlay requirements are tightened to below 5nm. Next to improvements in the immersion scanner platform, enhancements in the overlay optimization and process control are needed to enable these low overlay numbers. Whereas conventional overlay control methods address wafer and lot variation autonomously with wafer pre exposure alignment metrology and post exposure overlay metrology, we see a need to reduce these variations by correlating more of the TWINSCAN system's sensor data directly to the post exposure YieldStar metrology in time. In this paper we will present the results of a study on applying a real time control algorithm based on machine learning technology. Machine learning methods use context and TWINSCAN system sensor data paired with post exposure YieldStar metrology to recognize generic behavior and train the control system to anticipate on this generic behavior. Specific for this study, the data concerns immersion scanner context, sensor data and on-wafer measured overlay data. By making the link between the scanner data and the wafer data we are able to establish a real time relationship. The result is an inline controller that accounts for small changes in scanner hardware performance in time while picking up subtle lot to lot and wafer to wafer deviations introduced by wafer processing.

Incorporating Real-time Earthquake Information into Large Enrollment Natural Disaster Course Learning

Science.gov (United States)

Furlong, K. P.; Benz, H.; Hayes, G. P.; Villasenor, A.

2010-12-01

Although most would agree that the occurrence of natural disaster events such as earthquakes, volcanic eruptions, and floods can provide effective learning opportunities for natural hazards-based courses, implementing compelling materials into the large-enrollment classroom environment can be difficult. These natural hazard events derive much of their learning potential from their real-time nature, and in the modern 24/7 news-cycle where all but the most devastating events are quickly out of the public eye, the shelf life for an event is quite limited. To maximize the learning potential of these events requires that both authoritative information be available and course materials be generated as the event unfolds. Although many events such as hurricanes, flooding, and volcanic eruptions provide some precursory warnings, and thus one can prepare background materials to place the main event into context, earthquakes present a particularly confounding situation of providing no warning, but where context is critical to student learning. Attempting to implement real-time materials into large enrollment classes faces the additional hindrance of limited internet access (for students) in most lecture classrooms. In Earth 101 Natural Disasters: Hollywood vs Reality, taught as a large enrollment (150+ students) general education course at Penn State, we are collaborating with the USGS’s National Earthquake Information Center (NEIC) to develop efficient means to incorporate their real-time products into learning activities in the lecture hall environment. Over time (and numerous events) we have developed a template for presenting USGS-produced real-time information in lecture mode. The event-specific materials can be quickly incorporated and updated, along with key contextual materials, to provide students with up-to-the-minute current information. In addition, we have also developed in-class activities, such as student determination of population exposure to severe ground

Why Hong Kong students favour more face-to-face classroom time in blended learning

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James Henri

Full Text Available A three year study in student characteristics, needs and learning styles guided instructors at the University of Hong Kong Faculty of Education to improve teaching and learning in a core module: Information Literacy. A mixed-method approach analyzed data collected from undergraduate, in-service teachers in a BEd program, and helped instructors in the program to gain insight into the Hong Kong teacher working, post-service towards a BEd in Library and Information Science. Part-time students indicated a preference for a combination of online and face-to-face teaching, with more face-to-face class time in that mix. These findings would also be informative for other part-time programs using blended teaching and learning models.

Learning motion concepts using real-time microcomputer-based laboratory tools

Science.gov (United States)

Thornton, Ronald K.; Sokoloff, David R.

1990-09-01

Microcomputer-based laboratory (MBL) tools have been developed which interface to Apple II and Macintosh computers. Students use these tools to collect physical data that are graphed in real time and then can be manipulated and analyzed. The MBL tools have made possible discovery-based laboratory curricula that embody results from educational research. These curricula allow students to take an active role in their learning and encourage them to construct physical knowledge from observation of the physical world. The curricula encourage collaborative learning by taking advantage of the fact that MBL tools present data in an immediately understandable graphical form. This article describes one of the tools—the motion detector (hardware and software)—and the kinematics curriculum. The effectiveness of this curriculum compared to traditional college and university methods for helping students learn basic kinematics concepts has been evaluated by pre- and post-testing and by observation. There is strong evidence for significantly improved learning and retention by students who used the MBL materials, compared to those taught in lecture.

Cerebellar motor learning versus cerebellar motor timing: the climbing fibre story

Science.gov (United States)

Llinás, Rodolfo R

2011-01-01

Abstract Theories concerning the role of the climbing fibre system in motor learning, as opposed to those addressing the olivocerebellar system in the organization of motor timing, are briefly contrasted. The electrophysiological basis for the motor timing hypothesis in relation to the olivocerebellar system is treated in detail. PMID:21486816

EDUCATIONAL LEAPFROGGING IN THE mLEARNING TIME

Directory of Open Access Journals (Sweden)

Abdel Rahman IBRAHIM SULEIMAN

2014-07-01

Full Text Available In this theoretical study, researcher tries to shed light on the modern strategy of education, Mobile learning is this strategy, which has become a reality exists in the educational institutions and aims researcher of this study. Trying to figure out the reality of Mobil Determining if the mobile learning part of the E-Learning. Trying for identify future of mobile learning. And the researcher collect the information and the data from previous research in addition to what has been published on websites and blogs and has reached the researcher to achieve the successes of Mobile learning at the level of the educational process now , and that this strategy of mobile learning is not part of the e-learning, and generation of generations , but a new way for the development of the educational process educational , researcher is expected to evolve Mobile learning expands even at the all levels of educational.

Manifestations of Globalization and Linguistic Imperialism in English Language Teaching and Materials Preparation: Ideology in the International ELT Textbooks

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Seyyed Ali Kazemi

2017-09-01

Full Text Available This study intended to investigate the imposition of values and ideological patterns of particular societies affecting learners' identity as a result of globalization and linguistic imperialism in the internationally distributed textbooks which are developed to meet the English language needs of international learners and are broadly used in Islamic countries like Iran. It was important to work out whether violation of standards and ideological patterns of certain societies could be detected. For that reason, critical discourse analysis (CDA with its theory and procedures, as developed by Fairclough (1989, used in conversations, illustrations and reading passages in Interchange, Four Corners, Top Notch and American English File series and three meaning dimensions– the textbooks content, the social relations of the characters in the textbooks, and their subject positions– were classified and analyzed statistically. Overall, the findings of this study represented that these ELT books are by some means unfair and inclined to signify a specific discourse type, that is, the Western culture discourse, ideological patterns, and consumer societies, which can impose the Western view and have different effects on students' identity in Islamic countries.

INTEGRATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES IN TEACHING RUSSIAN AS A FOREIGN LANGUAGE FOR SPECIAL PURPOSES

OpenAIRE

Sergey S. Chromov; Nadezda A. Gulayeva; Irina S. Zelenetskaya

2015-01-01

The paper is untended to draw attention to information communication technologiesin teaching Russian as a foreign language for special purposes at level B 2. In thisregard the educational process of teaching Russian as a foreign language is examinedfor promoting quality improvement in the process of ELT.Technology-enhances language learning(TELL) is described through computer-assisted language learning(CALL)-presentations, webinars, videolectures. The authors share their experience obtained d...

Time-place learning and memory persist in mice lacking functional Per1 and Per2 clock genes.

Science.gov (United States)

Mulder, C; Van Der Zee, E A; Hut, R A; Gerkema, M P

2013-12-01

With time-place learning, animals link a stimulus with the location and the time of day. This ability may optimize resource localization and predator avoidance in daily changing environments. Time-place learning is a suitable task to study the interaction of the circadian system and memory. Previously, we showed that time-place learning in mice depends on the circadian system and Cry1 and/or Cry2 clock genes. We questioned whether time-place learning is Cry specific or also depends on other core molecular clock genes. Here, we show that Per1/Per2 double mutant mice, despite their arrhythmic phenotype, acquire time-place learning similar to wild-type mice. As well as an established role in circadian rhythms, Per genes have also been implicated in the formation and storage of memory. We found no deficiencies in short-term spatial working memory in Per mutant mice compared to wild-type mice. Moreover, both Per mutant and wild-type mice showed similar long-term memory for contextual features of a paradigm (a mild foot shock), measured in trained mice after a 2-month nontesting interval. In contrast, time-place associations were lost in both wild-type and mutant mice after these 2 months, suggesting a lack of maintained long-term memory storage for this type of information. Taken together, Cry-dependent time-place learning does not require Per genes, and Per mutant mice showed no PER-specific short-term or long-term memory deficiencies. These results limit the functional role of Per clock genes in the circadian regulation of time-place learning and memory.

Developing the metacognitive skill of noticing the gap through self-transcribing: The case of students enrolled in an ELT training program in Chile

Directory of Open Access Journals (Sweden)

Millaray D Salas

2015-10-01

Full Text Available This paper reports the preliminary results of the first phase of an ongoing educational intervention conducted with students enrolled in an ELT training program at PUCV. The study set out to explore the feasibility and effectiveness of the recording and self-transcription methodology (Lynch, 2001, 2007; Mennim, 2003, 2012 as a route to noticing the gap and defossilization. Students (N=20 transcribed the oral texts they produced during the speaking section of the diagnostic test for English 5. The tasks were: (1 transcribing three minutes of their speaking time, (2 highlighting all the errors they identified in their own speech (3 coding them (e.g. grammatical, lexical, phonological and (4 sending the annotated transcript to the instructor by email. Drawing on the theory of questionnaire design and processing (Dörnyei, 2003, a survey was designed and posted online (GoogleForm and emailed to the students. The questionnaire asked students to evaluate the perceived benefits of the self-transcription methodology. The study data consist of the annotated transcripts and the questionnaire responses. The results of this study were much less positive than what has been reported in the literature (Willis & Willis, 1996, Burns & Joyce, 1997; Lynch, 2001, 2007; Mennim, 2003, 2012; Thornbury & Slade, 2006; Boettinger, Park & Timmis 2010; Stillwell et al., 2010, so an attempt is made to see why this might have been the case. Some pedagogical implications of this approach in the Chilean context are discussed.

Teaching Reading Comprehension in English in a Distance Web-Based Course: New Roles for Teachers

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Jorge Hugo Muñoz Marín

2010-10-01

Full Text Available Distance web-based learning is a popular strategy in ELT teaching in Colombia. Despite of the growth of experiences, there are very few studies regarding teachers' participation in these courses. This paper reports preliminary findings of an on-going study aiming at exploring the roles that a teacher plays in an efl reading comprehension distance web-based course. Data analysis suggests that teachers play new roles solving technical problems, providing immediate feedback, interacting with students in a non traditional way, providing time management advice, and acting as a constant motivator. The authors conclude that EFL teachers require training for this new teaching roles and the analysis of web-based distance learning environments as an option under permanent construction that requires their active participation.

Blended learning pedagogy: the time is now!

Science.gov (United States)

Pizzi, Michael A

2014-07-01

Pedagogy is rapidly changing. To develop best practice in academia, it is important that we change with the changing needs of students. This article suggests that blended learning is one of the most important pedagogical formats that can enhance student learning, optimize the use of active learning strategies, and potentially improve student learning outcomes.

Key Vocabulary Learning Strategies in ESP And EGP Course Books

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Zahra Akbari

2015-01-01

Full Text Available An increasing body of research evidence is showing the advantages of using certain skills and behaviours called language learning strategies in general and vocabulary learning strategies (VLSs in particular in the process of L2 acquisition. University students who require reading English texts in their fields of study have to expand their vocabulary knowledge in a much more efficient way than ordinary ESL/EFL learners.  And ELT course books are a good place to incorporate learner training in this regard. The purpose of this study is to see how vocabulary learning strategies are treated in both the book designer's claims section and the exercises of English for Specific Purposes (ESP course books for students of medicine and para-medicine on the one hand and English for General Purposes (EGP course book used commonly by these students in Isfahan University of Medical Sciences, Isfahan, Iran on the other. In other words, the specified course books were analyzed based on the insights gained from VLS research to gauge the extent to which they have incorporated VLSs and training in using them. These books were published under the supervision of the center for studying and compiling university books in humanities (SAMT. Based on the review of the relevant literature, three key strategies were identified and an analytic framework was devised. The framework was then applied to the course books. It was found that the treatments in the specified course books were deemed unlikely to improve students’ abilities with these important skills and strategies.

A Computational Model of the Temporal Dynamics of Plasticity in Procedural Learning: Sensitivity to Feedback Timing

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Vivian V. Valentin

2014-07-01

Full Text Available The evidence is now good that different memory systems mediate the learning of different types of category structures. In particular, declarative memory dominates rule-based (RB category learning and procedural memory dominates information-integration (II category learning. For example, several studies have reported that feedback timing is critical for II category learning, but not for RB category learning – results that have broad support within the memory systems literature. Specifically, II category learning has been shown to be best with feedback delays of 500ms compared to delays of 0 and 1000ms, and highly impaired with delays of 2.5 seconds or longer. In contrast, RB learning is unaffected by any feedback delay up to 10 seconds. We propose a neurobiologically detailed theory of procedural learning that is sensitive to different feedback delays. The theory assumes that procedural learning is mediated by plasticity at cortical-striatal synapses that are modified by dopamine-mediated reinforcement learning. The model captures the time-course of the biochemical events in the striatum that cause synaptic plasticity, and thereby accounts for the empirical effects of various feedback delays on II category learning.

KOMPARASI KEMAMPUAN KOMUNIKASI MATEMATIS SISWA DENGAN MODEL LEARNING CYCLE DAN TIME TOKEN

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Arin Ayundhita

2014-11-01

Full Text Available Tujuan penelitian ini untuk mengetahui apakah model pembelajaran Learning Cycle 5E dan model pembelajaran Time Token pada siswa kelas VIII materi keliling dan luas lingkaran dapat mencapai ketuntasan belajar dan untuk mengetahui manakah yang lebih baik antara model pembelajaran Learning Cycle 5E dan model pembelajaran Time Token. Populasi dalam penelitian ini adalah siswa kelas VIII SMP Negeri 1 Sine Kabupaten Ngawi tahun pelajaran 2013/2014. Dengan menggunakan teknik cluster random sampling, terpilih sampel yaitu siswa kelas VIII A sebagai kelas eksperimen 1 dan kelas VIII E sebagai kelas eksperimen 2. Pengumpulan data dilakukan dengan metode dokumentasi, tes, dan observasi. Analisis data menggunakan uji proporsi dan uji perbedaan dua rata-rata. Dari hasil uji ketuntasan belajar diperoleh siswa kelas eksperimen 1 mencapai ketuntasan belajar klasikal sementara kelas eksperimen 2 belum mencapai ketuntasan belajar klasikal. Dari hasil uji perbedaan rata-rata satu pihak diperoleh rata-rata kemampuan komunikasi matematis siswa kelas eksperimen 1 lebih baik daripada rata-rata kemampuan komunikasi matematis siswa kelas eksperimen 2. Simpulan yang diperoleh adalah model pembelajaran Learning Cycle 5E lebih baik dari pembelajaran dengan model Time Token.

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

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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.

Real time eye tracking using Kalman extended spatio-temporal context learning

Science.gov (United States)

Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

2017-06-01

Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

Neuromodulated Spike-Timing-Dependent Plasticity and Theory of Three-Factor Learning Rules

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Wulfram eGerstner

2016-01-01

Full Text Available Classical Hebbian learning puts the emphasis on joint pre- and postsynaptic activity, but neglects the potential role of neuromodulators. Since neuromodulators convey information about novelty or reward, the influence of neuromodulatorson synaptic plasticity is useful not just for action learning in classical conditioning, but also to decide 'when' to create new memories in response to a flow of sensory stimuli.In this review, we focus on timing requirements for pre- and postsynaptic activity in conjunction with one or several phasic neuromodulatory signals. While the emphasis of the text is on conceptual models and mathematical theories, we also discusssome experimental evidence for neuromodulation of Spike-Timing-Dependent Plasticity.We highlight the importance of synaptic mechanisms in bridging the temporal gap between sensory stimulation and neuromodulatory signals, and develop a framework for a class of neo-Hebbian three-factor learning rules that depend on presynaptic activity, postsynaptic variables as well as the influence of neuromodulators.

ENGLISH LANGUAGE TEACHING IN ISLAMIC EDUCATION IN INDONESIA; CHALLENGES AND OPPORTUNITIES

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Tuti Hidayati

2016-05-01

Full Text Available The dominant use of English in every field covering politic, economic, and sosial culture these days has manifested in its gaining a special position in many countries where it is not spoken. In Indonesia, it is a foreign language officially constituted as part of national education curriculum and becomes a requirement in a number of higher education and workforce entry. Yet, ELT in Indonesia faces various constraints including, but is not limited, the anxiousness to threat the purity of Bahasa Indonesia, the national language, and the worry about liberal western values embedded in English to corrupt the youngsters moral and attitudes. Interestingly, Islamic education that maintains a vital role among Indonesians has included English alongside other secular sciences and technology as part of its curriculum in its current advancement. In this regard, the paper will show how critical Islamic education role among Indonesians is, how ELT in Indonesia has developed, what challenges it experiences, and what opportunities it posseses in the context of Indonesian Islamic Education. The paper argues that Islamic education remains the choice of the Indonesian Muslim communities as long as it is able to meet the demands of living in the globalization era while keeping the Islamic values in all the learning process. It further suggests that ELT in Indonesia needs to incorporate Islamic values and show that English learning put no threats and negative influences to Indonesian culture in general and Islamic religious values in particular.

Prospective EFL Teachers' Perceptions of Listening Comprehension Problems in Turkey

Science.gov (United States)

Solak, Ekrem; Altay, Firat

2014-01-01

Listening skill has been called as the "Cinderella Skill" which is overlooked by its elder sister speaking in language learning. Therefore, the purpose of the study was to reemphasize the importance of listening skill in ELT context and to determine prospective English teachers' perceptions of listening comprehension problems. The study…

Experiments with Online Reinforcement Learning in Real-Time Strategy Games

DEFF Research Database (Denmark)

Toftgaard Andersen, Kresten; Zeng, Yifeng; Dahl Christensen, Dennis

2009-01-01

Real-time strategy (RTS) games provide a challenging platform to implement online reinforcement learning (RL) techniques in a real application. Computer, as one game player, monitors opponents' (human or other computers) strategies and then updates its own policy using RL methods. In this article......, we first examine the suitability of applying the online RL in various computer games. Reinforcement learning application depends on both RL complexity and the game features. We then propose a multi-layer framework for implementing online RL in an RTS game. The framework significantly reduces RL...... the effectiveness of our proposed framework and shed light on relevant issues in using online RL in RTS games....

CAT-PUMA: CME Arrival Time Prediction Using Machine learning Algorithms

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Liu, Jiajia; Ye, Yudong; Shen, Chenglong; Wang, Yuming; Erdélyi, Robert

2018-04-01

CAT-PUMA (CME Arrival Time Prediction Using Machine learning Algorithms) quickly and accurately predicts the arrival of Coronal Mass Ejections (CMEs) of CME arrival time. The software was trained via detailed analysis of CME features and solar wind parameters using 182 previously observed geo-effective partial-/full-halo CMEs and uses algorithms of the Support Vector Machine (SVM) to make its predictions, which can be made within minutes of providing the necessary input parameters of a CME.

Blended language learning: An effective solution but not without its challenges

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Christopher Johnson

2014-09-01

Full Text Available The study discussed in this investigation is part of a larger collaborative initiative between Laureate Education and Cambridge University Press (LEP-CUP collaboration. This second phase of the research, completed in 2013, aimed to further explore the conclusions from phase 1 and set out to identify effective and appropriate best practice blended learning models within the network. A study was set up with 36 teachers, all experienced ELT teachers with differing levels of experience in blended language teaching, who took part in extended focus groups discussions sessions prompted by a series of questions. Responses from these groups of teachers indicated that a flipped classroom model is beginning to develop. The authors of this study found evidence of changing approaches to language teaching, changes that are not without their challenges, but for a number of the teachers who participated in this research sample these changes are bringing considerable benefit to their teaching experience. This study offered teachers another opportunity to become change managers for students who need to acquire the autonomous, life-long learning skills of the 21st as they transition into professional life. The scope of this study cannot address and solve all of the issues involved in this process, but it provides a step towards that end. DOI: 10.18870/hlrc.v4i3.213

Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

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Lee, Hanbong

2016-01-01

Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

Tensorial dynamic time warping with articulation index representation for efficient audio-template learning.

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Le, Long N; Jones, Douglas L

2018-03-01

Audio classification techniques often depend on the availability of a large labeled training dataset for successful performance. However, in many application domains of audio classification (e.g., wildlife monitoring), obtaining labeled data is still a costly and laborious process. Motivated by this observation, a technique is proposed to efficiently learn a clean template from a few labeled, but likely corrupted (by noise and interferences), data samples. This learning can be done efficiently via tensorial dynamic time warping on the articulation index-based time-frequency representations of audio data. The learned template can then be used in audio classification following the standard template-based approach. Experimental results show that the proposed approach outperforms both (1) the recurrent neural network approach and (2) the state-of-the-art in the template-based approach on a wildlife detection application with few training samples.

Precarious Learning and Labour in Financialized Times

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Jamie Magnusson

2013-07-01

Full Text Available Our current globalized economic regimes of financialized capital have systematically altered relations of learning and labour through the dynamics of precarity, debt, and the political economy of new wars. The risks of these regimes are absorbed unevenly across transnational landscapes, creating cartographies of violence and dispossession, particularly among youth, indigenous, working class, and racialized women. Presently there is surprisingly little discussion on the relevance of financialization for adult educators. Transnational resistances organizing against neoliberal restructuring, austerity policies, and debt crises are emerging at the same time that massive investments are being made into homeland security and the carceral state. This paper opens up discussion on the implications of financialized times for educators, and develops an analytic framework for examining how these global realities are best addressed at local sites of adult and higher education.

An Evaluation of American English File Series

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Behnam Ghasemi

2012-03-01

Full Text Available Textbooks play a pivotal role in language learning classrooms. The problem is that among a wide range of textbooks in market which is appropriate for a specific classroom and a group of learners. In order to evaluate ELT textbooks theorists and writers have offered different kinds of evaluative frameworks based on a number of principles and criteria. This study evaluates a series of ELT textbook, namely, American English File by the use of Littlejohn’s (1998 evaluative framework to see what explicit features of the book are, what pedagogic values it has, whether it is in line with its claimed objectives, and what its merits and demerits are. Littlejohn believes that we should evaluate a textbook based on its own pedagogic values and we should see what is in it not what teacher and evaluators think must exist in it. Consequently his framework is claimed to be devoid of any impressionistic ideas and it is in-depth and objective rather than being subjective. Nine ELT experts and ten ELT teachers helped the researcher rate the evaluative checklists. The results of the study show that although a number of shortcomings and drawbacks were found in American English File, it stood up reasonably well to a detailed and in-depth analysis and that its pedagogic values and positive attributes far out-weighed its shortcomings. The internal consistency between ratings was computed via the statistical tool of Cronbach’s alpha that indicated a desirable inter-rater reliability.

Concept of Best Practices in English Language Teaching to Pakistani ELT Fraternity

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Muhammad Arif Soomro

2016-08-01

Full Text Available Teaching industry of English as a second or foreign language has grown massively in recent times in Pakistan. There are many public sectors universities and English academies established all over Pakistan offering English language proficiency courses. Therefore, this wave led to conduct this research. The purpose of conducting this study was to investigate contemporary pedagogical techniques used for teaching and learning English and to introduce the concept of ESL /EFL Best Practices for effective language teaching in Pakistan. Purposive Sampling method was used to collect the information from respondents regarding their contemporary-used teaching techniques in ESL/EFL class. The questionnaire was implied as the main tool for data collection among twenty English language teachers from two public sector universities. The results of the study indicated that teachers were attached  with some outdated techniques and activities secondly, they also faced problems applying new techniques while teaching in a large multilevel classrooms, thirdly, teachers’ had willingness to adopt and employ innovative techniques in classrooms and lastly, the notion of ESL best practices was uncommon among them. Most of the teaching strategies do not create better learning environment, and learners do not interestingly participate due outdated activities. Therefore, the suggested solution was utilizing best practices that are based on modern techniques, approaches considerable for multiple levels depending upon the needs and developmental state of the individual learners. Keywords: pedagogical strategies, ESL/EFL Best Practices, Pakistani teachers, English teaching/learning

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.

Kinesthetic Astronomy: Significant Upgrades to the Sky Time Lesson that Support Student Learning

Science.gov (United States)

Morrow, C. A.; Zawaski, M.

2004-12-01

This paper will report on a significant upgrade to the first in a series of innovative, experiential lessons we call Kinesthetic Astronomy. The Sky Time lesson reconnects students with the astronomical meaning of the day, year, and seasons. Like all Kinesthetic Astronomy lessons, it teaches basic astronomical concepts through choreographed bodily movements and positions that provide educational sensory experiences. They are intended for sixth graders up through adult learners in both formal and informal educational settings. They emphasize astronomical concepts and phenomenon that people can readily encounter in their "everyday" lives such as time, seasons, and sky motions of the Sun, Moon, stars, and planets. Kinesthetic Astronomy lesson plans are fully aligned with national science education standards, both in content and instructional practice. Our lessons offer a complete learning cycle with written assessment opportunities now embedded throughout the lesson. We have substantially strengthened the written assessment options for the Sky Time lesson to help students translate their kinesthetic and visual learning into the verbal-linguistic and mathematical-logical realms of expression. Field testing with non-science undergraduates, middle school science teachers and students, Junior Girl Scouts, museum education staff, and outdoor educators has been providing evidence that Kinesthetic Astronomy techniques allow learners to achieve a good grasp of concepts that are much more difficult to learn in more conventional ways such as via textbooks or even computer animation. Field testing of the Sky Time lesson has also led us to significant changes from the previous version to support student learning. We will report on the nature of these changes.

Increasing Student Intrinsic Motivation and Self-Efficacy through Gamification Pedagogy

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Banfield, James; Wilkerson, Brad

2014-01-01

The aim of this study was to assess gamification as a method of experiential learning theory (ELT) on student motivation and self-efficacy to perform System Engineering/Information Assurance (IA) tasks. The study was a basic qualitative method, whereby data was collected via semi-structured interview and then analyzed for recurring themes and…

Evaluation of WorldView Textbooks; Textbooks Taught at a Military University

Science.gov (United States)

Khalili, Masoud; Jodai, Hojat

2012-01-01

This paper intends to evaluate the WorldView series textbooks of English learning, which are being taught at an Iranian military university foreign language center. No textbook evaluation had been conducted by the university administration prior to the introduction of the textbooks to the language program. Theorists in the field of ELT textbook…

A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

Science.gov (United States)

Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

2016-12-01

Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

Feasibility of a real-time hand hygiene notification machine learning system in outpatient clinics.

Science.gov (United States)

Geilleit, R; Hen, Z Q; Chong, C Y; Loh, A P; Pang, N L; Peterson, G M; Ng, K C; Huis, A; de Korne, D F

2018-04-09

Various technologies have been developed to improve hand hygiene (HH) compliance in inpatient settings; however, little is known about the feasibility of machine learning technology for this purpose in outpatient clinics. To assess the effectiveness, user experiences, and costs of implementing a real-time HH notification machine learning system in outpatient clinics. In our mixed methods study, a multi-disciplinary team co-created an infrared guided sensor system to automatically notify clinicians to perform HH just before first patient contact. Notification technology effects were measured by comparing HH compliance at baseline (without notifications) with real-time auditory notifications that continued till HH was performed (intervention I) or notifications lasting 15 s (intervention II). User experiences were collected during daily briefings and semi-structured interviews. Costs of implementation of the system were calculated and compared to the current observational auditing programme. Average baseline HH performance before first patient contact was 53.8%. With real-time auditory notifications that continued till HH was performed, overall HH performance increased to 100% (P machine learning system were estimated to be 46% lower than the observational auditing programme. Machine learning technology that enables real-time HH notification provides a promising cost-effective approach to both improving and monitoring HH, and deserves further development in outpatient settings. Copyright © 2018 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Working and Learning in Times of Uncertainty

DEFF Research Database (Denmark)

This book analyses the challenges of globalisation and uncertainty impacting on working and learning at individual, organisational and societal levels. Each of the contributions addresses two overall questions: How is working and learning affected by uncertainty and globalisation? And, in what ways...... do individuals, organisations, political actors and education systems respond to these challenges? Part 1 focuses on the micro level of working and learning for understanding the learning processes from an individual point of view by reflecting on learners’ needs and situations at work and in school......). Finally, Part 3 addresses the macro level of working and learning by analysing how to govern, structure and organise vocational, professional and adult education at the boundaries of work, education and policy making....

Examining the Effect of Time Constraint on the Online Mastery Learning Approach towards Improving Postgraduate Students' Achievement

Science.gov (United States)

Ee, Mong Shan; Yeoh, William; Boo, Yee Ling; Boulter, Terry

2018-01-01

Time control plays a critical role within the online mastery learning (OML) approach. This paper examines the two commonly implemented mastery learning strategies--personalised system of instructions and learning for mastery (LFM)--by focusing on what occurs when there is an instructional time constraint. Using a large data set from a postgraduate…

A Study of Time Spent Working at Learning Centers. Technical Report #17.

Science.gov (United States)

Omori, Sharon; And Others

This study examined the proportion of time children in the Kamehameha Early Education Program schools spend at actual school work in learning centers. Systematic time-sampled observations using multiple observers were conducted in December-January and again in March-April. The subjects, 12 children (6 kindergarteners and 6 first graders) were…

Ectopic lymphoid tissues support local immunoglobulin production in patients with chronic rhinosinusitis with nasal polyps.

Science.gov (United States)

Song, Jia; Wang, Hai; Zhang, Ya-Na; Cao, Ping-Ping; Liao, Bo; Wang, Zhe-Zheng; Shi, Li-Li; Yao, Yin; Zhai, Guan-Ting; Wang, Zhi-Chao; Liu, Li-Meng; Zeng, Ming; Lu, Xiang; Wang, Heng; Yang, Xiang-Ping; Yu, Di; Bachert, Claus; Liu, Zheng

2018-03-01

The contribution of ectopic lymphoid tissues (eLTs) to local immunoglobulin hyperproduction in patients with chronic rhinosinusitis with nasal polyps (CRSwNP) is unclear. We sought to explore the cellular basis, formation mechanisms, and function of eLTs in patients with CRSwNP. We graded lymphoid aggregations in sinonasal mucosa and histologically studied their structures. The expression of lymphorganogenic factors and molecules required for immunoglobulin production was measured by using real-time PCR, and their localization was analyzed by means of immunohistochemistry and immunofluorescence. The phenotype of follicular helper T cells was analyzed by performing flow cytometry. Immunoglobulin levels were quantified by using the Bio-Plex assay or ImmunoCAP system. Nasal tissue explants were challenged ex vivo with Dermatophagoides pteronyssinus group 1 (Der p 1), and the expression of Iε-Cμ and Iε-Cγ circle transcripts was detected by using seminested PCR. Increased formation of eLTs with germinal center-like structures was discovered in patients with eosinophilic (20.69%) and noneosinophilic (17.31%) CRSwNP compared with that in patients with chronic rhinosinusitis without nasal polyps (5.66%) and control subjects (3.70%). The presence of eLTs was associated with increased expression of lymphorganogenic and inflammatory chemokines and cytokines, as well as their receptors. The expression of molecules required for immunoglobulin production, generation of follicular helper T cells, and production of IgE in eosinophilic polyps and IgG and IgA in both eosinophilic and noneosinophilic polyps were predominantly upregulated in patients with eLTs. After Der p 1 challenge ex vivo, Iε-Cμ transcript was detected only in eosinophilic polyps with eLTs but not in polyps without eLTs and noneosinophilic polyps. eLTs might support local immunoglobulin production and therefore significantly contribute to the development of CRSwNP. Copyright © 2017 American Academy of

Dynamic Hebbian Cross-Correlation Learning Resolves the Spike Timing Dependent Plasticity Conundrum

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Tjeerd V. olde Scheper

2018-01-01

Full Text Available Spike Timing-Dependent Plasticity has been found to assume many different forms. The classic STDP curve, with one potentiating and one depressing window, is only one of many possible curves that describe synaptic learning using the STDP mechanism. It has been shown experimentally that STDP curves may contain multiple LTP and LTD windows of variable width, and even inverted windows. The underlying STDP mechanism that is capable of producing such an extensive, and apparently incompatible, range of learning curves is still under investigation. In this paper, it is shown that STDP originates from a combination of two dynamic Hebbian cross-correlations of local activity at the synapse. The correlation of the presynaptic activity with the local postsynaptic activity is a robust and reliable indicator of the discrepancy between the presynaptic neuron and the postsynaptic neuron's activity. The second correlation is between the local postsynaptic activity with dendritic activity which is a good indicator of matching local synaptic and dendritic activity. We show that this simple time-independent learning rule can give rise to many forms of the STDP learning curve. The rule regulates synaptic strength without the need for spike matching or other supervisory learning mechanisms. Local differences in dendritic activity at the synapse greatly affect the cross-correlation difference which determines the relative contributions of different neural activity sources. Dendritic activity due to nearby synapses, action potentials, both forward and back-propagating, as well as inhibitory synapses will dynamically modify the local activity at the synapse, and the resulting STDP learning rule. The dynamic Hebbian learning rule ensures furthermore, that the resulting synaptic strength is dynamically stable, and that interactions between synapses do not result in local instabilities. The rule clearly demonstrates that synapses function as independent localized

Information extraction from dynamic PS-InSAR time series using machine learning

Science.gov (United States)

van de Kerkhof, B.; Pankratius, V.; Chang, L.; van Swol, R.; Hanssen, R. F.

2017-12-01

Due to the increasing number of SAR satellites, with shorter repeat intervals and higher resolutions, SAR data volumes are exploding. Time series analyses of SAR data, i.e. Persistent Scatterer (PS) InSAR, enable the deformation monitoring of the built environment at an unprecedented scale, with hundreds of scatterers per km2, updated weekly. Potential hazards, e.g. due to failure of aging infrastructure, can be detected at an early stage. Yet, this requires the operational data processing of billions of measurement points, over hundreds of epochs, updating this data set dynamically as new data come in, and testing whether points (start to) behave in an anomalous way. Moreover, the quality of PS-InSAR measurements is ambiguous and heterogeneous, which will yield false positives and false negatives. Such analyses are numerically challenging. Here we extract relevant information from PS-InSAR time series using machine learning algorithms. We cluster (group together) time series with similar behaviour, even though they may not be spatially close, such that the results can be used for further analysis. First we reduce the dimensionality of the dataset in order to be able to cluster the data, since applying clustering techniques on high dimensional datasets often result in unsatisfying results. Our approach is to apply t-distributed Stochastic Neighbor Embedding (t-SNE), a machine learning algorithm for dimensionality reduction of high-dimensional data to a 2D or 3D map, and cluster this result using Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The results show that we are able to detect and cluster time series with similar behaviour, which is the starting point for more extensive analysis into the underlying driving mechanisms. The results of the methods are compared to conventional hypothesis testing as well as a Self-Organising Map (SOM) approach. Hypothesis testing is robust and takes the stochastic nature of the observations into account

The Role of Age and Occupational Future Time Perspective in Workers' Motivation to Learn

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Kochoian, Nané; Raemdonck, Isabel; Frenay, Mariane; Zacher, Hannes

2017-01-01

The purpose of this paper is to better understand the relationship between employees' chronological age and their motivation to learn, by adopting a lifespan perspective. Based on socioemotional selectivity theory, we suggest that occupational future time perspective mediates the relationship between age and motivation to learn. In accordance with…

Determination of the Ecological and Geographic Distributions of Armillaria Species in Missouri Ozark Forest Ecosystems

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Johann N. Bruhn; James J. Wetteroff; Jeanne D. Mihail; Susan. Burks

1997-01-01

Armillaria root rot contributes to oak decline in the Ozarks. Three Armillaria species were detected in Ecological Landtypes (ELT's) representing south- to west-facing side slopes (ELT 17), north- to east-facing side slopes (ELT 18), and ridge tops (ELT 11). Armillaria mellea was detected in 91 percent...

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

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Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

The difference of delay time in monitoring system of facial acupressure learning media using bluetooth, wireless and ethernet

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Agustin, Eny Widhia; Hangga, Arimaz; Fahrian, Muhammad Iqbal; Azhari, Anis Fikri

2018-03-01

The implementation of monitoring system in the facial acupressure learning media could increase the students' proficiency. However the common learning media still has not implemented a monitoring system in their learning process. This research was conducted to implement monitoring system in the mannequin head prototype as a learning media of facial acupressure using Bluetooth, wireless and Ethernet. The results of the implementation of monitoring system in the prototype showed that there were differences in the delay time between Bluetooth and wireless or Ethernet. The results data showed no difference in the average delay time between the use of Bluetooth with wireless and the use of Bluetooth with Ethernet in monitoring system of facial acupressure learning media. From all the facial acupressure points, the forehead facial acupressure point has the longest delay time of 11.93 seconds. The average delay time in all 3 class rooms was 1.96 seconds therefore the use of Bluetooth, wireless and Ethernet is highly recommended in the monitoring system of facial acupressure.

Approach to the E-ELT dome and main structure challenges

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Bilbao, Armando; Murga, Gaizka; Gómez, Celia; Llarena, Javier

2014-07-01

The E-ELT as a whole could be classified as an extremely challenging project. More precisely, it should be defined as an array of many different sub-challenges, which comprise technical, logistical and managerial matters. This paper reviews some of these critical challenges, in particular those related to the Dome and the Main Structure, suggesting ways to face them in the most pragmatic way possible. Technical challenges for the Dome and the Main Structure are mainly related to the need to upscale current design standards to an order of magnitude larger design. Trying a direct design escalation is not feasible; it would not work. A design effort is needed to cross hybridize current design standards with technologies coming from other different applications. Innovative design is therefore not a wish but a must. And innovative design comes along with design risk. Design risk needs to be tackled from two angles: on the one hand through thorough design validation analysis and on the other hand through extensive pre-assembly and testing. And, once again, full scale integrated pre-assembly and testing of extremely large subsystems is not always possible. Therefore, defining a comprehensive test plan for critical components, critical subsystems and critical subassemblies becomes essential. Logistical challenges are linked to the erection site. Cerro Armazones is a remote site and this needs to be considered when evaluating transport and erection requirements. But it is not only the remoteness of the site that needs to be considered. The size of both Dome and Main Structure require large construction cranes and a well defined erection plan taking into account pre-assembly strategies, limited plan area utilization, erection sequence, erection stability during intermediate stages and, very specifically, efficient coordination between the Dome and the Main Structure erection processes. Managerial issues pose another set of challenges in this project. Both the size of the

Teachers' Attitudes towards Teaching English Grammar: A Scale Development Study

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Polat, Murat

2017-01-01

In most ELT classes, the importance of grammar, how it should be taught or how much it should be integrated into language teaching are still matters of discussion. Considering this fact, learning teachers' attitudes towards teaching grammar is significantly valuable for researchers. This study thus aimed to design a scale that identifies teachers'…

Emotional Intelligence in Language Instruction in Oman: The Missing Link?

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Balasubramanian, Chandrika; Al-Mahrooqi, Rahma

2016-01-01

The field of English Language Teaching (ELT) has long sought to identify traits of good language learners, in an effort to teach these traits to less successful language learners (Rubin, 1975). Emotional Intelligence has recently come to the forefront of research on language learning and teaching, and is now increasingly recognized as an important…

An investigation of fMRI time series stationarity during motor sequence learning foot tapping tasks.

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Muhei-aldin, Othman; VanSwearingen, Jessie; Karim, Helmet; Huppert, Theodore; Sparto, Patrick J; Erickson, Kirk I; Sejdić, Ervin

2014-04-30

Understanding complex brain networks using functional magnetic resonance imaging (fMRI) is of great interest to clinical and scientific communities. To utilize advanced analysis methods such as graph theory for these investigations, the stationarity of fMRI time series needs to be understood as it has important implications on the choice of appropriate approaches for the analysis of complex brain networks. In this paper, we investigated the stationarity of fMRI time series acquired from twelve healthy participants while they performed a motor (foot tapping sequence) learning task. Since prior studies have documented that learning is associated with systematic changes in brain activation, a sequence learning task is an optimal paradigm to assess the degree of non-stationarity in fMRI time-series in clinically relevant brain areas. We predicted that brain regions involved in a "learning network" would demonstrate non-stationarity and may violate assumptions associated with some advanced analysis approaches. Six blocks of learning, and six control blocks of a foot tapping sequence were performed in a fixed order. The reverse arrangement test was utilized to investigate the time series stationarity. Our analysis showed some non-stationary signals with a time varying first moment as a major source of non-stationarity. We also demonstrated a decreased number of non-stationarities in the third block as a result of priming and repetition. Most of the current literature does not examine stationarity prior to processing. The implication of our findings is that future investigations analyzing complex brain networks should utilize approaches robust to non-stationarities, as graph-theoretical approaches can be sensitive to non-stationarities present in data. Copyright © 2014 Elsevier B.V. All rights reserved.

Instructional Advice, Time Advice and Learning Questions in Computer Simulations

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Rey, Gunter Daniel

2010-01-01

Undergraduate students (N = 97) used an introductory text and a computer simulation to learn fundamental concepts about statistical analyses (e.g., analysis of variance, regression analysis and General Linear Model). Each learner was randomly assigned to one cell of a 2 (with or without instructional advice) x 2 (with or without time advice) x 2…

Through Teachers’ Eyes: The Use of Virtual Classrooms in ELT

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Jairo Enrique Castañeda

2012-12-01

Full Text Available The use of virtual environments to support as well as to complement language teaching and learning processes is becoming a recurrent practice and sometimes policy in several educational institutions. This paper reports the results of an inquiry carried out at the language center of a private university in Bogotá. Those results intended to describe EFL teachers’ viewpoints regarding the promotion of autonomous, collaborative, and meaningful learning through the use of virtual classrooms in the teaching of English as a foreign language. Findings show that the promotion of these three types of learning through the use of virtual classrooms still represents challenges in the context in which this study was carried out.

The Effect of Inquiry Training Learning Model Based on Just in Time Teaching for Problem Solving Skill

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Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda

2016-01-01

One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…

THE FLIPPED WRITING CLASSROOM IN TURKISH EFL CONTEXT: A COMPARATIVE STUDY ON A NEW MODEL

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Emrah EKMEKCI

2017-04-01

Full Text Available Flipped learning, one of the most popular and conspicuous instructional models of recent time, can be considered as a pedagogical approach in which the typical lecture and homework elements of a course are reversed. Flipped learning transforms classrooms into interactive and dynamic places where the teacher guides the students and facilitates their learning. The current study explores the impact of flipped instruction on students’ foreign language writing skill which is often perceived as boring, complex and difficult by English as a Foreign Language (EFL learners. The study compares flipped and traditional face-to-face writing classes on the basis of writing performances. Employing a pre- and post-test true experimental design with a control group, the study is based on a mixed-method research. The experimental group consisting of 23 English Language Teaching (ELT students attending preparatory class were instructed for fifteen weeks through Flipped Writing Class Model while the control group comprising 20 ELT preparatory class students followed traditional face-to-face lecture-based writing class. Independent and paired samples t-tests were carried out for the analyses of the data gathered through the pre-and post-tests. The results indicated that there was a statistically significant difference between the experimental and control groups in terms of their writing performances based on the employed rubric. It was found that the students in the experimental group outperformed the students in the control group after the treatment process. The results of the study also revealed that the great majority of the students in the experimental group held positive attitudes towards Flipped Writing Class Model.

UV induction of the LT-Toxin operon with respect to the genes lexA, recA, and umuD

International Nuclear Information System (INIS)

Tiganova, I.G.; Rusina, O.Yu.; Andreeva, I.V.; Brukhanskii, G.V.; Skavronskaya, A.G.

1994-01-01

UV induction of the elt operon (the LT-toxin operon in Escherichia coli) was demonstrated in experiments using fusion of elt::lac operons with the help of Mud1(Ap lac) phage. UV induction of the elt operon is lexA-dependent; thus, the possibility of SOS regulation of this process may be assumed. However, UV induction of the elt operon turned out to be recA-independent, which makes it impossible to consider this induction as a typical SOS response. UV induction of the elt operon is also observed in Salmonella typhimurium, which differs from E. coli in the product of umuD, which suggests that the UV induction of the elt operon is umuD independent

Unsupervised Learning of Digit Recognition Using Spike-Timing-Dependent Plasticity

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Peter U. Diehl

2015-08-01

Full Text Available In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns, since most of such SNN architectures rely on training in a rate-based network and subsequent conversion to a SNN. We present a SNN for digit recognition which is based on mechanisms with increased biological plausibility, i.e. conductance-based instead of current-based synapses, spike-timing-dependent plasticity with time-dependent weight change, lateral inhibition, and an adaptive spiking threshold. Unlike most other systems, we do not use a teaching signal and do not present any class labels to the network. Using this unsupervised learning scheme, our architecture achieves 95% accuracy on the MNIST benchmark, which is better than previous SNN implementations without supervision. The fact that we used no domain-specific knowledge points toward the general applicability of our network design. Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks.

Implicit leadership theories in applied settings: factor structure, generalizability, and stability over time.

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Epitropaki, Olga; Martin, Robin

2004-04-01

The present empirical investigation had a 3-fold purpose: (a) to cross-validate L. R. Offermann, J. K. Kennedy, and P. W. Wirtz's (1994) scale of Implicit Leadership Theories (ILTs) in several organizational settings and to further provide a shorter scale of ILTs in organizations; (b) to assess the generalizability of ILTs across different employee groups, and (c) to evaluate ILTs' change over time. Two independent samples were used for the scale validation (N1 = 500 and N2 = 439). A 6-factor structure (Sensitivity, Intelligence, Dedication, Dynamism, Tyranny, and Masculinity) was found to most accurately represent ELTs in organizational settings. Regarding the generalizability of ILTs, although the 6-factor structure was consistent across different employee groups, there was only partial support for total factorial invariance. Finally, evaluation of gamma, beta, and alpha change provided support for ILTs' stability over time.

Time to Engage? Texting to Support and Enhance First Year Undergraduate Learning

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Geraldine Jones

2009-04-01

Full Text Available In this paper we discuss a case study investigating how the academic and personal development of first year students on an undergraduate sports education degree can be supported and enhanced with mobile SMS communication. SMS-based technologies were introduced in response to students’ particular needs (in transition to Higher Education and characteristics (‘digital natives’. Despite being unaccustomed to using their mobile phones for academic study, students willingly participated in SMS communication with their tutor via a texting management service. Drawing on evidence from two student surveys, focus groups and a tutor’s journal, we illustrate the potential that mobile SMS communication has to link and establish continuity between face to face teaching sessions and online learning activities in the Virtual Learning Environment (VLE. Many students perceived the SMS communication to have had a positive impact on their management of study time. We link our findings with the existing literature and argue that mobile text based communication has the potential to support the development of time management skills, an important component of self regulatory learning, a skill which has been shown to be key in making a successful transition.

Teaching Reading Comprehension in English in a Distance Web-Based Course: New Roles for Teachers (La enseñanza de la comprensión de lectura en inglés en un curso a distancia en la red: nuevos roles para los docentes)

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Muñoz Marín, Jorge Hugo; González Moncada, Adriana

2010-01-01

Distance web-based learning is a popular strategy in ELT teaching in Colombia. Despite of the growth of experiences, there are very few studies regarding teachers' participation in these courses. This paper reports preliminary findings of an on-going study aiming at exploring the roles that a teach er plays in an EFL reading comprehension distance…

English Language Teaching Research in South Korea: A Review of Recent Studies (2009-2014)

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Moodie, Ian; Nam, Hyun-Jeong

2016-01-01

This article reviews recent studies on English language teaching (ELT) in South Korea, where a great deal of research has been produced in recent years in local journals. In this article we review 95 studies from a pool of some 1,200 published between 2009 and 2014 on English language teaching and learning, focusing on research within the public…

The 3 R's of Learning Time: Rethink, Reshape, Reclaim

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Sackey, Shera Carter

2012-01-01

The Learning School Alliance is a network of schools collaborating about professional practice. The network embodies Learning Forward's purpose to advance effective job-embedded professional learning that leads to student outcomes. A key component of Learning Forward's Standards for Professional Learning is a focus on collaborative learning,…

Do learning collaboratives strengthen communication? A comparison of organizational team communication networks over time.

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Bunger, Alicia C; Lengnick-Hall, Rebecca

Collaborative learning models were designed to support quality improvements, such as innovation implementation by promoting communication within organizational teams. Yet the effect of collaborative learning approaches on organizational team communication during implementation is untested. The aim of this study was to explore change in communication patterns within teams from children's mental health organizations during a year-long learning collaborative focused on implementing a new treatment. We adopt a social network perspective to examine intraorganizational communication within each team and assess change in (a) the frequency of communication among team members, (b) communication across organizational hierarchies, and (c) the overall structure of team communication networks. A pretest-posttest design compared communication among 135 participants from 21 organizational teams at the start and end of a learning collaborative. At both time points, participants were asked to list the members of their team and rate the frequency of communication with each along a 7-point Likert scale. Several individual, pair-wise, and team level communication network metrics were calculated and compared over time. At the individual level, participants reported communicating with more team members by the end of the learning collaborative. Cross-hierarchical communication did not change. At the team level, these changes manifested differently depending on team size. In large teams, communication frequency increased, and networks grew denser and slightly less centralized. In small teams, communication frequency declined, growing more sparse and centralized. Results suggest that team communication patterns change minimally but evolve differently depending on size. Learning collaboratives may be more helpful for enhancing communication among larger teams; thus, managers might consider selecting and sending larger staff teams to learning collaboratives. This study highlights key future

Learning about Learning: Action Learning in Times of Organisational Change

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Hill, Robyn

2009-01-01

This paper explores the conduct and outcomes of an action learning activity during a period of intense organisational change in a medium-sized vocational education and training organisation in Victoria, Australia. This organisation was the subject of significant change due to government-driven and statewide amalgamation, downsizing and sector…

Training haptic stiffness discrimination: time course of learning with or without visual information and knowledge of results.

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Teodorescu, Kinneret; Bouchigny, Sylvain; Korman, Maria

2013-08-01

In this study, we explored the time course of haptic stiffness discrimination learning and how it was affected by two experimental factors, the addition of visual information and/or knowledge of results (KR) during training. Stiffness perception may integrate both haptic and visual modalities. However, in many tasks, the visual field is typically occluded, forcing stiffness perception to be dependent exclusively on haptic information. No studies to date addressed the time course of haptic stiffness perceptual learning. Using a virtual environment (VE) haptic interface and a two-alternative forced-choice discrimination task, the haptic stiffness discrimination ability of 48 participants was tested across 2 days. Each day included two haptic test blocks separated by a training block Additional visual information and/or KR were manipulated between participants during training blocks. Practice repetitions alone induced significant improvement in haptic stiffness discrimination. Between days, accuracy was slightly improved, but decision time performance was deteriorated. The addition of visual information and/or KR had only temporary effects on decision time, without affecting the time course of haptic discrimination learning. Learning in haptic stiffness discrimination appears to evolve through at least two distinctive phases: A single training session resulted in both immediate and latent learning. This learning was not affected by the training manipulations inspected. Training skills in VE in spaced sessions can be beneficial for tasks in which haptic perception is critical, such as surgery procedures, when the visual field is occluded. However, training protocols for such tasks should account for low impact of multisensory information and KR.

What time is it? Deep learning approaches for circadian rhythms.

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Agostinelli, Forest; Ceglia, Nicholas; Shahbaba, Babak; Sassone-Corsi, Paolo; Baldi, Pierre

2016-06-15

Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken. We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic signals. We then use deep learning methods to develop and train BIO_CYCLE, a system to robustly estimate which signals are periodic in high-throughput circadian experiments, producing estimates of amplitudes, periods, phases, as well as several statistical significance measures. Using the curated data, BIO_CYCLE is compared to other approaches and shown to achieve state-of-the-art performance across multiple metrics. We then use deep learning methods to develop and train BIO_CLOCK to robustly estimate the time at which a particular single-time-point transcriptomic experiment was carried. In most cases, BIO_CLOCK can reliably predict time, within approximately 1 h, using the expression levels of only a small number of core clock genes. BIO_CLOCK is shown to work reasonably well across tissue types, and often with only small degradation across conditions. BIO_CLOCK is used to annotate most mouse experiments found in the GEO database with an inferred time stamp. All data and software are publicly available on the CircadiOmics web portal: circadiomics.igb.uci.edu/ fagostin@uci.edu or pfbaldi@uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Upper Extremity Motor Learning among Individuals with Parkinson's Disease: A Meta-Analysis Evaluating Movement Time in Simple Tasks

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K. Felix

2012-01-01

Full Text Available Motor learning has been found to occur in the rehabilitation of individuals with Parkinson's disease (PD. Through repetitive structured practice of motor tasks, individuals show improved performance, confirming that motor learning has probably taken place. Although a number of studies have been completed evaluating motor learning in people with PD, the sample sizes were small and the improvements were variable. The purpose of this meta-analysis was to determine the ability of people with PD to learn motor tasks. Studies which measured movement time in upper extremity reaching tasks and met the inclusion criteria were included in the analysis. Results of the meta-analysis indicated that people with PD and neurologically healthy controls both demonstrated motor learning, characterized by a decrease in movement time during upper extremity movements. Movement time improvements were greater in the control group than in individuals with PD. These results support the findings that the practice of upper extremity reaching tasks is beneficial in reducing movement time in persons with PD and has important implications for rehabilitation.

THE IMPACT OF SOCIAL MEDIA ON VOCABULARY LEARNING

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Sim Monica-Ariana

2014-12-01

Full Text Available The paper aims at investigating the impact of computer and social media in improving students’ knowledge of English language namely vocabulary acquisition (focused on Facebook with intermediate and upper intermediate first and second year ELT students in Economics at the Faculty of Economic Sciences, University of Oradea. Social media technologies take on many different forms including magazines, Internet forums, weblogs, social blogs, wikis, social networks, podcasts, pictures, videos etc. Technologies cover blogging, picture-sharing, wall-posting, music-sharing just to name a few. Nowadays Facebook technology seems to play an important part for the social life of so many becoming more and more popular as a main means of communication, that it could also meet an educational need. Thus it could play a distinguished role in foreign language learning and teaching. Several studies investigate using different technologies in learning and teaching, in particular, foreign language learning. Still, rare studies were interested precisely in the role of Facebook in learning foreign languages. In this study was intended to assess the role and effectiveness of Facebook use in vocabulary learning. Particularly, the research attempts to answer the question: Can social media affect students’ development and progress in the foreign language?’ In order to discover the answer to this question of the study, a project based on Facebook for the experimental group was conceived. It was assumed that significant differences were to be found between the groups using social media for learning purposes and those who did not in developing vocabulary knowledge. The study was conducted with a number of 127 students of the Faculty of Economic Sciences, University of Oradea, 1st and 2nd year students following the specializations: International Business, Management, Marketing, Finances studying in the academic year 2013-2014. The development in each group was measured

Using Online Lectures to Make Time for Active Learning

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Prunuske, Amy J.; Batzli, Janet; Howell, Evelyn; Miller, Sarah

2012-01-01

To make time in class for group activities devoted to critical thinking, we integrated a series of short online lectures into the homework assignments of a large, introductory biology course at a research university. The majority of students viewed the online lectures before coming to class and reported that the online lectures helped them to complete the in-class activity and did not increase the amount of time they devoted to the course. In addition, students who viewed the online lecture performed better on clicker questions designed to test lower-order cognitive skills. The in-class activities then gave the students practice analyzing the information in groups and provided the instructor with feedback about the students’ understanding of the material. On the basis of the results of this study, we support creating hybrid course models that allow students to learn the fundamental information outside of class time, thereby creating time during the class period to be dedicated toward the conceptual understanding of the material. PMID:22714412

Incoherent dictionary learning for reducing crosstalk noise in least-squares reverse time migration

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Wu, Juan; Bai, Min

2018-05-01

We propose to apply a novel incoherent dictionary learning (IDL) algorithm for regularizing the least-squares inversion in seismic imaging. The IDL is proposed to overcome the drawback of traditional dictionary learning algorithm in losing partial texture information. Firstly, the noisy image is divided into overlapped image patches, and some random patches are extracted for dictionary learning. Then, we apply the IDL technology to minimize the coherency between atoms during dictionary learning. Finally, the sparse representation problem is solved by a sparse coding algorithm, and image is restored by those sparse coefficients. By reducing the correlation among atoms, it is possible to preserve most of the small-scale features in the image while removing much of the long-wavelength noise. The application of the IDL method to regularization of seismic images from least-squares reverse time migration shows successful performance.

Evidence for an alternation strategy in time-place learning.

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Pizzo, Matthew J; Crystal, Jonathon D

2004-11-30

Many different conclusions concerning what type of mechanism rats use to solve a daily time-place task have emerged in the literature. The purpose of this study was to test three competing explanations of time-place discrimination. Rats (n = 10) were tested twice daily in a T-maze, separated by approximately 7 h. Food was available at one location in the morning and another location in the afternoon. After the rats learned to visit each location at the appropriate time, tests were omitted to evaluate whether the rats were utilizing time-of-day (i.e., a circadian oscillator) or an alternation strategy (i.e., visiting a correct location is a cue to visit the next location). Performance on this test was significantly lower than chance, ruling out the use of time-of-day. A phase advance of the light cycle was conducted to test the alternation strategy and timing with respect to the light cycle (i.e., an interval timer). There was no difference between probe and baseline performance. These results suggest that the rats used an alternation strategy to meet the temporal and spatial contingencies in the time-place task.

Giving English Language Learners the Time They Need to Succeed: Profiles of Three Expanded Learning Time Schools

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Farbman, David A.

2015-01-01

With the number of students who are English language learners (ELLs) likely to double in coming years, it is more important than ever for schools across the U.S. to design and implement educational practices and strategies that best meet ELLs' learning needs, says the report, "Giving English Language Learners the Time They Need to…

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

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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

Lessons Learned from Real-Time, Event-Based Internet Science Communications

Science.gov (United States)

Phillips, T.; Myszka, E.; Gallagher, D. L.; Adams, M. L.; Koczor, R. J.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

For the last several years the Science Directorate at Marshall Space Flight Center has carried out a diverse program of Internet-based science communication. The Directorate's Science Roundtable includes active researchers, NASA public relations, educators, and administrators. The Science@NASA award-winning family of Web sites features science, mathematics, and space news. The program includes extended stories about NASA science, a curriculum resource for teachers tied to national education standards, on-line activities for students, and webcasts of real-time events. The focus of sharing science activities in real-time has been to involve and excite students and the public about science. Events have involved meteor showers, solar eclipses, natural very low frequency radio emissions, and amateur balloon flights. In some cases, broadcasts accommodate active feedback and questions from Internet participants. Through these projects a pattern has emerged in the level of interest or popularity with the public. The pattern differentiates projects that include science from those that do not, All real-time, event-based Internet activities have captured public interest at a level not achieved through science stories or educator resource material exclusively. The worst event-based activity attracted more interest than the best written science story. One truly rewarding lesson learned through these projects is that the public recognizes the importance and excitement of being part of scientific discovery. Flying a camera to 100,000 feet altitude isn't as interesting to the public as searching for viable life-forms at these oxygen-poor altitudes. The details of these real-time, event-based projects and lessons learned will be discussed.

Using Just-in-Time Information to Support Scientific Discovery Learning in a Computer-Based Simulation

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Hulshof, Casper D.; de Jong, Ton

2006-01-01

Students encounter many obstacles during scientific discovery learning with computer-based simulations. It is hypothesized that an effective type of support, that does not interfere with the scientific discovery learning process, should be delivered on a "just-in-time" base. This study explores the effect of facilitating access to…

Learning Management System Calendar Reminders and Effects on Time Management and Academic Performance

Science.gov (United States)

Mei, Jianyang

2016-01-01

This research project uses a large research university in the Midwest as a research site to explore the time management skills of international students and analyzes how using the Course Hack, an online Learning Management System (LMS) calendar tool, improves participants' time management skills and positively impacts their academic performance,…

Time to learn: the outlook for renewal of patient-centred education in the digital age.

Science.gov (United States)

Glick, T H; Moore, G T

2001-05-01

Major forces in society and within health systems are fragmenting patient care and clinical learning. The distancing of physician and trainee from the patient undermines learning about the patient-doctor relationship. The disconnection of care and learning from one successive venue to another impedes the ability of trainees to learn about illness longitudinally. As a conceptual piece, our methods have been those of witnessing the experiences of patients, practitioners, and students over time and observing the impact of fragmented systems and changing expectations on care and learning. We have reflected on the opportunities created by digital information systems and interactive telemedicine to help renew essential relationships. Although there is, as yet, little in the literature on educational or health outcomes of this kind of technological enablement, we anticipate opportunities for a renewed focus on the patient in that patient's own space and time. Multimedia applications can achieve not only real-time connections, but can help construct a "virtual patient" as a platform for supervision and assessment, permitting preceptors to evaluate trainee-patient interactions, utilization of Web-based data and human resources, and on-line professionalism. Just as diverse elements in society are capitalizing upon digital technology to create advantageous relationships, all of the elements in the complex systems of health care and medical training can be better connected, so as to put the patient back in the centre of care and the trainee's ongoing relationship to the patient back in the centre of education.

Learning Constructive Primitives for Real-time Dynamic Difficulty Adjustment in Super Mario Bros

OpenAIRE

Shi, Peizhi; Chen, Ke

2017-01-01

Among the main challenges in procedural content generation (PCG), content quality assurance and dynamic difficulty adjustment (DDA) of game content in real time are two major issues concerned in adaptive content generation. Motivated by the recent learning-based PCG framework, we propose a novel approach to seamlessly address two issues in Super Mario Bros (SMB). To address the quality assurance issue, we exploit the synergy between rule-based and learning-based methods to produce quality gam...

Car-following Behavior Model Learning Using Timed Automata

NARCIS (Netherlands)

Zhang, Yihuan; Lin, Q.; Wang, Jun; Verwer, S.E.; Dochain, D.; Henrion, D.; Peaucelle, D.

Learning driving behavior is fundamental for autonomous vehicles to “understand” traffic situations. This paper proposes a novel method for learning a behavioral model of car-following using automata learning algorithms. The model is interpretable for car-following behavior analysis. Frequent common

Focusing on Student Learning to Guide the Use of Staff Time

Science.gov (United States)

Bates, Imelda; Baume, David; Assinder, Susan

2010-01-01

The paper develops and illustrates a model for designing courses. The model gives explicit attention to educational considerations, principally to the importance of active, goal-directed student learning. It also explores economic considerations, principally how to make the best possible use of the time of the teacher in planning and running the…

Real-time learning of predictive recognition categories that chunk sequences of items stored in working memory

Directory of Open Access Journals (Sweden)

Stephen eGrossberg

2014-10-01

Full Text Available How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list

Online discussion compensates for suboptimal timing of supportive information presentation in a digitally supported learning environment

NARCIS (Netherlands)

Noroozi, O.; Busstra, M.C.; Mulder, M.; Biemans, H.J.A.; Tobi, H.; Geelen, A.; Veer, van 't P.; Chizari, M.

2012-01-01

This study used a sequential set-up to investigate the consecutive effects of timing of supportive information presentation (information before vs. information during the learning task clusters) in interactive digital learning materials (IDLMs) and type of collaboration (personal discussion vs.

Large-scale machine learning and evaluation platform for real-time traffic surveillance

Science.gov (United States)

Eichel, Justin A.; Mishra, Akshaya; Miller, Nicholas; Jankovic, Nicholas; Thomas, Mohan A.; Abbott, Tyler; Swanson, Douglas; Keller, Joel

2016-09-01

In traffic engineering, vehicle detectors are trained on limited datasets, resulting in poor accuracy when deployed in real-world surveillance applications. Annotating large-scale high-quality datasets is challenging. Typically, these datasets have limited diversity; they do not reflect the real-world operating environment. There is a need for a large-scale, cloud-based positive and negative mining process and a large-scale learning and evaluation system for the application of automatic traffic measurements and classification. The proposed positive and negative mining process addresses the quality of crowd sourced ground truth data through machine learning review and human feedback mechanisms. The proposed learning and evaluation system uses a distributed cloud computing framework to handle data-scaling issues associated with large numbers of samples and a high-dimensional feature space. The system is trained using AdaBoost on 1,000,000 Haar-like features extracted from 70,000 annotated video frames. The trained real-time vehicle detector achieves an accuracy of at least 95% for 1/2 and about 78% for 19/20 of the time when tested on ˜7,500,000 video frames. At the end of 2016, the dataset is expected to have over 1 billion annotated video frames.

Ensemble Deep Learning for Biomedical Time Series Classification

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Lin-peng Jin

2016-01-01

Full Text Available Ensemble learning has been proved to improve the generalization ability effectively in both theory and practice. In this paper, we briefly outline the current status of research on it first. Then, a new deep neural network-based ensemble method that integrates filtering views, local views, distorted views, explicit training, implicit training, subview prediction, and Simple Average is proposed for biomedical time series classification. Finally, we validate its effectiveness on the Chinese Cardiovascular Disease Database containing a large number of electrocardiogram recordings. The experimental results show that the proposed method has certain advantages compared to some well-known ensemble methods, such as Bagging and AdaBoost.

Supervised spike-timing-dependent plasticity: a spatiotemporal neuronal learning rule for function approximation and decisions.

Science.gov (United States)

Franosch, Jan-Moritz P; Urban, Sebastian; van Hemmen, J Leo

2013-12-01

How can an animal learn from experience? How can it train sensors, such as the auditory or tactile system, based on other sensory input such as the visual system? Supervised spike-timing-dependent plasticity (supervised STDP) is a possible answer. Supervised STDP trains one modality using input from another one as "supervisor." Quite complex time-dependent relationships between the senses can be learned. Here we prove that under very general conditions, supervised STDP converges to a stable configuration of synaptic weights leading to a reconstruction of primary sensory input.

Communication, timing, and common learning

Czech Academy of Sciences Publication Activity Database

Steiner, Jakub; Stewart, C.

2011-01-01

Roč. 146, č. 1 (2011), s. 230-247 ISSN 0022-0531 Institutional research plan: CEZ:AV0Z70850503 Keywords : common knowledge * learning * communication Subject RIV: AH - Economics Impact factor: 1.235, year: 2011

Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

Science.gov (United States)

Parsa, Maryam; Panda, Priyadarshini; Sen, Shreyas; Roy, Kaushik

2017-07-01

Recent progress in biosensor technology and wearable devices has created a formidable opportunity for remote healthcare monitoring systems as well as real-time diagnosis and disease prevention. The use of data mining techniques is indispensable for analysis of the large pool of data generated by the wearable devices. Deep learning is among the promising methods for analyzing such data for healthcare applications and disease diagnosis. However, the conventional deep neural networks are computationally intensive and it is impractical to use them in real-time diagnosis with low-powered on-body devices. We propose Staged Inference using Conditional Deep Learning (SICDL), as an energy efficient approach for creating healthcare monitoring systems. For smart diagnostics, we observe that all diagnoses are not equally challenging. The proposed approach thus decomposes the diagnoses into preliminary analysis (such as healthy vs unhealthy) and detailed analysis (such as identifying the specific type of cardio disease). The preliminary diagnosis is conducted real-time with a low complexity neural network realized on the resource-constrained on-body device. The detailed diagnosis requires a larger network that is implemented remotely in cloud and is conditionally activated only for detailed diagnosis (unhealthy individuals). We evaluated the proposed approach using available physiological sensor data from Physionet databases, and achieved 38% energy reduction in comparison to the conventional deep learning approach.

A real-time standard parts inspection based on deep learning

Science.gov (United States)

Xu, Kuan; Li, XuDong; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Since standard parts are necessary components in mechanical structure like bogie and connector. These mechanical structures will be shattered or loosen if standard parts are lost. So real-time standard parts inspection systems are essential to guarantee their safety. Researchers would like to take inspection systems based on deep learning because it works well in image with complex backgrounds which is common in standard parts inspection situation. A typical inspection detection system contains two basic components: feature extractors and object classifiers. For the object classifier, Region Proposal Network (RPN) is one of the most essential architectures in most state-of-art object detection systems. However, in the basic RPN architecture, the proposals of Region of Interest (ROI) have fixed sizes (9 anchors for each pixel), they are effective but they waste much computing resources and time. In standard parts detection situations, standard parts have given size, thus we can manually choose sizes of anchors based on the ground-truths through machine learning. The experiments prove that we could use 2 anchors to achieve almost the same accuracy and recall rate. Basically, our standard parts detection system could reach 15fps on NVIDIA GTX1080 (GPU), while achieving detection accuracy 90.01% mAP.

Learning the language of time: Children's acquisition of duration words.

Science.gov (United States)

Tillman, Katharine A; Barner, David

2015-05-01

Children use time words like minute and hour early in development, but take years to acquire their precise meanings. Here we investigate whether children assign meaning to these early usages, and if so, how. To do this, we test their interpretation of seven time words: second, minute, hour, day, week, month, and year. We find that preschoolers infer the orderings of time words (e.g., hour>minute), but have little to no knowledge of the absolute durations they encode. Knowledge of absolute duration is learned much later in development - many years after children first start using time words in speech - and in many children does not emerge until they have acquired formal definitions for the words. We conclude that associating words with the perception of duration does not come naturally to children, and that early intuitive meanings of time words are instead rooted in relative orderings, which children may infer from their use in speech. Copyright © 2015 Elsevier Inc. All rights reserved.

A Virtual Learning Environment for Part-Time MASW Students: An Evaluation of the WebCT

Science.gov (United States)

Chan, Charles C.; Tsui, Ming-sum; Chan, Mandy Y. C.; Hong, Joe H.

2008-01-01

This study aims to evaluate the perception of a cohort of social workers studying for a part-time master's program in social work in using the popular Web-based learning platform--World Wide Web Course Tools (WebCT) as a complimentary method of teaching and learning. It was noted that social work profession began incorporating computer technology…

Language Learning Attitudes: Ingrained Or Shaped In Time?

Directory of Open Access Journals (Sweden)

Gökçe DİŞLEN DAĞGÖL

2017-09-01

Full Text Available Language learning has become an essential need in today’s world. From academic to social settings, humans need to communicate in a different language to survive in their community. However, despite this increasing importance of language, it is difficult to say we have attained successful language learning on a large scale since there are a lot of factors in language learning process. Language attitudes, one of these factors, influence this process both positively and negatively, depending on how we view learning a foreign language. Therefore, this study deals with the issue of language attitudes to uncover learners’ language conceptions and probable effects on their learning. Moreover, this study aims to reveal the potential role of past learning experiences on the development of language beliefs positively or negatively. Thus, 35 university students in their 1st, 2nd, 3rd and 4th years constitute the participants of the study. Based on mixed research design, the study is comprised of both quantitative and qualitative data. Quantitative data were gathered through Attitude Scale towards English Course, and the analyses were performed with Statistical Packages for Social Sciences (SPSS 17.0 version for Windows. The qualitative data were collected from students’ reports of their own autobiographies regarding their previous language learning experiences in elementary, secondary, high school and university years, and were subjected to the content analysis. The study showed language attitudes from behavioural, cognitive and affective perspectives and found out different factors in shaping their learning conceptions.

CLIL activities by Liz Dale and Rosie Tanner

OpenAIRE

Simpson, Adam John

2012-01-01

Ever since David Marsh and Anne Maljers ushered in the era of CLIL in 1994, this new methodology has remained a source of hot debate in ELT. While many teachers are suspicious of or indeed resistant to the very notion of Content and Language Integrated learning, others view it as the future of language teaching. For those unfamiliar with the concept, CLIL is an approach which aims to marry the learning of content to the acquisition of an additional language, thus teaching both the subject and...

Time-place learning over a lifetime : Absence of memory loss in trained old mice

NARCIS (Netherlands)

Mulder, Cornelis K; Reckman, Gerlof A R; Gerkema, Menno P; van der Zee, Eddy A

Time-place learning (TPL) offers the possibility to study the functional interaction between cognition and the circadian system with aging. With TPL, animals link biological significant events with the location and the time of day. This what-where-when type of memory provides animals with an

Enhancement of Online Robotics Learning Using Real-Time 3D Visualization Technology

Directory of Open Access Journals (Sweden)

Richard Chiou

2010-06-01

Full Text Available This paper discusses a real-time e-Lab Learning system based on the integration of 3D visualization technology with a remote robotic laboratory. With the emergence and development of the Internet field, online learning is proving to play a significant role in the upcoming era. In an effort to enhance Internet-based learning of robotics and keep up with the rapid progression of technology, a 3- Dimensional scheme of viewing the robotic laboratory has been introduced in addition to the remote controlling of the robots. The uniqueness of the project lies in making this process Internet-based, and remote robot operated and visualized in 3D. This 3D system approach provides the students with a more realistic feel of the 3D robotic laboratory even though they are working remotely. As a result, the 3D visualization technology has been tested as part of a laboratory in the MET 205 Robotics and Mechatronics class and has received positive feedback by most of the students. This type of research has introduced a new level of realism and visual communications to online laboratory learning in a remote classroom.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

Science.gov (United States)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Machine learning in heart failure: ready for prime time.

Science.gov (United States)

Awan, Saqib Ejaz; Sohel, Ferdous; Sanfilippo, Frank Mario; Bennamoun, Mohammed; Dwivedi, Girish

2018-03-01

The aim of this review is to present an up-to-date overview of the application of machine learning methods in heart failure including diagnosis, classification, readmissions and medication adherence. Recent studies have shown that the application of machine learning techniques may have the potential to improve heart failure outcomes and management, including cost savings by improving existing diagnostic and treatment support systems. Recently developed deep learning methods are expected to yield even better performance than traditional machine learning techniques in performing complex tasks by learning the intricate patterns hidden in big medical data. The review summarizes the recent developments in the application of machine and deep learning methods in heart failure management.

Why Hong Kong students favour more face-to-face classroom time in blended learning

OpenAIRE

Henri,James; Lee,Sandra

2007-01-01

A three year study in student characteristics, needs and learning styles guided instructors at the University of Hong Kong Faculty of Education to improve teaching and learning in a core module: Information Literacy. A mixed-method approach analyzed data collected from undergraduate, in-service teachers in a BEd program, and helped instructors in the program to gain insight into the Hong Kong teacher working, post-service towards a BEd in Library and Information Science. Part-time students in...

Procedural learning is impaired in dyslexia: Evidence from a meta-analysis of serial reaction time studies☆

Science.gov (United States)

Lum, Jarrad A.G.; Ullman, Michael T.; Conti-Ramsden, Gina

2013-01-01

A number of studies have investigated procedural learning in dyslexia using serial reaction time (SRT) tasks. Overall, the results have been mixed, with evidence of both impaired and intact learning reported. We undertook a systematic search of studies that examined procedural learning using SRT tasks, and synthesized the data using meta-analysis. A total of 14 studies were identified, representing data from 314 individuals with dyslexia and 317 typically developing control participants. The results indicate that, on average, individuals with dyslexia have worse procedural learning abilities than controls, as indexed by sequence learning on the SRT task. The average weighted standardized mean difference (the effect size) was found to be 0.449 (CI95: .204, .693), and was significant (p dyslexia. PMID:23920029

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Directory of Open Access Journals (Sweden)

Jianbo Qian

2013-01-01

Full Text Available We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them in O(n4 time. For some important special cases, the time complexity can be improved to be O(n2 using dynamic programming techniques.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

Science.gov (United States)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

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

Science.gov (United States)

Grossberg, Stephen

2015-09-24

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

Real-time Stereoscopic 3D for E-Robotics Learning

Directory of Open Access Journals (Sweden)

Richard Y. Chiou

2011-02-01

Full Text Available Following the design and testing of a successful 3-Dimensional surveillance system, this 3D scheme has been implemented into online robotics learning at Drexel University. A real-time application, utilizing robot controllers, programmable logic controllers and sensors, has been developed in the “MET 205 Robotics and Mechatronics” class to provide the students with a better robotic education. The integration of the 3D system allows the students to precisely program the robot and execute functions remotely. Upon the students’ recommendation, polarization has been chosen to be the main platform behind the 3D robotic system. Stereoscopic calculations are carried out for calibration purposes to display the images with the highest possible comfort-level and 3D effect. The calculations are further validated by comparing the results with students’ evaluations. Due to the Internet-based feature, multiple clients have the opportunity to perform the online automation development. In the future, students, in different universities, will be able to cross-control robotic components of different types around the world. With the development of this 3D ERobotics interface, automation resources and robotic learning can be shared and enriched regardless of location.

An integrated theory of prospective time interval estimation : The role of cognition, attention, and learning

NARCIS (Netherlands)

Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John

A theory of prospective time perception is introduced and incorporated as a module in an integrated theory of cognition, thereby extending existing theories and allowing predictions about attention and learning. First, a time perception module is established by fitting existing datasets (interval

Time-Place Learning over a Lifetime: Absence of Memory Loss in Trained Old Mice

Science.gov (United States)

Mulder, Cornelis K.; Reckman, Gerlof A. R.; Gerkema, Menno P.; Van der Zee, Eddy A.

2015-01-01

Time-place learning (TPL) offers the possibility to study the functional interaction between cognition and the circadian system with aging. With TPL, animals link biological significant events with the location and the time of day. This what-where-when type of memory provides animals with an experience-based daily schedule. Mice were tested for…

Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training

Directory of Open Access Journals (Sweden)

Alexandru D. Iordan

2018-01-01

Full Text Available Growing evidence suggests that healthy aging affects the configuration of large-scale functional brain networks. This includes reducing network modularity and local efficiency. However, the stability of these effects over time and their potential role in learning remain poorly understood. The goal of the present study was to further clarify previously reported age effects on “resting-state” networks, to test their reliability over time, and to assess their relation to subsequent learning during training. Resting-state fMRI data from 23 young (YA and 20 older adults (OA were acquired in 2 sessions 2 weeks apart. Graph-theoretic analyses identified both consistencies in network structure and differences in module composition between YA and OA, suggesting topological changes and less stability of functional network configuration with aging. Brain-wide, OA showed lower modularity and local efficiency compared to YA, consistent with the idea of age-related functional dedifferentiation, and these effects were replicable over time. At the level of individual networks, OA consistently showed greater participation and lower local efficiency and within-network connectivity in the cingulo-opercular network, as well as lower intra-network connectivity in the default-mode network and greater participation of the somato-sensorimotor network, suggesting age-related differential effects at the level of specialized brain modules. Finally, brain-wide network properties showed associations, albeit limited, with learning rates, as assessed with 10 days of computerized working memory training administered after the resting-state sessions, suggesting that baseline network configuration may influence subsequent learning outcomes. Identification of neural mechanisms associated with learning-induced plasticity is important for further clarifying whether and how such changes predict the magnitude and maintenance of training gains, as well as the extent and limits of

A longitudinal study on time perspectives: relations with academic delay of gratification and learning environment

NARCIS (Netherlands)

Peetsma, T.; Schuitema, J.; van der Veen, I.

2012-01-01

After they start secondary school (at age 12 in the Netherlands), students' time perspectives on school and professional career and self-regulated learning decrease, while their perspectives on leisure increase. We aimed to investigate relations in the developments in time perspectives and delay of

Changes in recognition memory over time: an ERP investigation into vocabulary learning.

Directory of Open Access Journals (Sweden)

Shekeila D Palmer

Full Text Available Although it seems intuitive to assume that recognition memory fades over time when information is not reinforced, some aspects of word learning may benefit from a period of consolidation. In the present study, event-related potentials (ERP were used to examine changes in recognition memory responses to familiar and newly learned (novel words over time. Native English speakers were taught novel words associated with English translations, and subsequently performed a Recognition Memory task in which they made old/new decisions in response to both words (trained word vs. untrained word, and novel words (trained novel word vs. untrained novel word. The Recognition task was performed 45 minutes after training (Day 1 and then repeated the following day (Day 2 with no additional training session in between. For familiar words, the late parietal old/new effect distinguished old from new items on both Day 1 and Day 2, although response to trained items was significantly weaker on Day 2. For novel words, the LPC again distinguished old from new items on both days, but the effect became significantly larger on Day 2. These data suggest that while recognition memory for familiar items may fade over time, recognition of novel items, conscious recollection in particular may benefit from a period of consolidation.

A Social Practice Theory of Learning and Becoming across Contexts and Time

Science.gov (United States)

Penuel, William R.; DiGiacomo, Daniela K.; Van Horne, Katie; Kirshner, Ben

2016-01-01

This paper presents a social practice theory of learning and becoming across contexts and time. Our perspective is rooted in the Danish tradition of critical psychology (Dreier, 1997; Mørck & Huniche, 2006; Nissen, 2005), and we use social practice theory to interpret the pathway of one adolescent whom we followed as part of a longitudinal…

Optimizing Earth Data Search Ranking using Deep Learning and Real-time User Behaviour

Science.gov (United States)

Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; McGibbney, L. J.; Greguska, F. R., III

2017-12-01

Finding Earth science data has been a challenging problem given both the quantity of data available and the heterogeneity of the data across a wide variety of domains. Current search engines in most geospatial data portals tend to induce end users to focus on one single data characteristic dimension (e.g., term frequency-inverse document frequency (TF-IDF) score, popularity, release date, etc.). This approach largely fails to take account of users' multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset out of a vast range of available datasets. With users interacting with search engines, sufficient information is already hidden in the log files. Compared with explicit feedback data, information that can be derived/extracted from log files is virtually free and substantially more timely. In this dissertation, I propose an online deep learning framework that can quickly update the learning function based on real-time user clickstream data. The contributions of this framework include 1) a log processor that can ingest, process and create training data from web logs in a real-time manner; 2) a query understanding module to better interpret users' search intent using web log processing results and metadata; 3) a feature extractor that identifies ranking features representing users' multidimensional interests of geospatial data; and 4) a deep learning based ranking algorithm that can be trained incrementally using user behavior data. The search ranking results will be evaluated using precision at K and normalized discounted cumulative gain (NDCG).

Leading Learning in Our Times

Science.gov (United States)

Trilling, Bernie

2010-01-01

Important tools that schools need to support a 21st century approach to teaching and learning include the usual suspects: the Internet, pen and paper, cell phones, educational games, tests and quizzes, good teachers, caring communities, educational funding, and loving parents. All of these items and more contribute to a 21st century education, but…

An attempt to elaborate a construct to measure the degree of explicitness and implicitness in ELT materials

Directory of Open Access Journals (Sweden)

Pascual Cantos Gómez

2010-06-01

Full Text Available The concepts of explicit and implicit (knowledge are at the core of SLA studies. We take explicit as conscious and declarative (knowledge; implicit as unconscious, automatic and procedural (knowledge (DeKeyser, 2003; R. Ellis, 2005a, 2005b, 2009; Hulstjin, 2005; Robinson, 1996; Schmidt, 1990, 1994. The importance of those concepts and components, we believe, must also be acknowledged in language teaching, and consequently in language teaching materials. However, explicitness and implicitness are rather complex constructs; such complexity allows for multiple nuances and perspectives in their analysis, and this fact poses a real challenge for their identification in the learning and teaching process and materials. We focus here on ELT materials and aim at the building of a reliable construct which may help in the identification of their potential for promoting implicit and explicit components. We first determined the features to identify the construct for implicitness and explicitness; next, we validated it and then we applied it to the analysis of the activities included in three sample units of three textbooks. The results were computed along a continuum ranging from 0 to 10 in each activity. The systematization and computation of results will hopefully offer a reliable figure regarding the identification of the degree of explicitness and/or implicitness in the materials analysed.Los conceptos de (conocimiento explícito e implícito constituyen uno de los puntos centrales en los estudios sobre la adquisición de lenguas extranjeras. Por explícito se entiende (conocimiento consciente o declarativo; por implícito, (conocimiento no consciente, automático y procedimentalizado (DeKeyser, 2003; R. Ellis, 2005a, 2005b, 2009; Hulstjin, 2005; Robinson, 1996; Schmidt, 1990, 1994. La importancia de ambos conceptos debe trasladarse también al campo de la enseñanza de idiomas y por lo tanto a los materiales docentes. Sin embargo, lo explícito e impl

A real-time articulatory visual feedback approach with target presentation for second language pronunciation learning.

Science.gov (United States)

Suemitsu, Atsuo; Dang, Jianwu; Ito, Takayuki; Tiede, Mark

2015-10-01

Articulatory information can support learning or remediating pronunciation of a second language (L2). This paper describes an electromagnetic articulometer-based visual-feedback approach using an articulatory target presented in real-time to facilitate L2 pronunciation learning. This approach trains learners to adjust articulatory positions to match targets for a L2 vowel estimated from productions of vowels that overlap in both L1 and L2. Training of Japanese learners for the American English vowel /æ/ that included visual training improved its pronunciation regardless of whether audio training was also included. Articulatory visual feedback is shown to be an effective method for facilitating L2 pronunciation learning.

An Integrated Theory of Prospective Time Interval Estimation: The Role of Cognition, Attention, and Learning

Science.gov (United States)

Taatgen, Niels A.; van Rijn, Hedderik; Anderson, John

2007-01-01

A theory of prospective time perception is introduced and incorporated as a module in an integrated theory of cognition, thereby extending existing theories and allowing predictions about attention and learning. First, a time perception module is established by fitting existing datasets (interval estimation and bisection and impact of secondary…

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Science.gov (United States)

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Science.gov (United States)

Bao, Wei; Yue, Jun; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

In Pursuit of Alternatives in ELT Methodology: WebQuests

Science.gov (United States)

Sen, Ayfer; Neufeld, Steve

2006-01-01

Although the Internet has opened up a vast new source of information for university students to use and explore, many students lack the skills to find, critically evaluate and intelligently exploit web-based resources. This problem is accentuated in English-medium universities where students learn and use English as a foreign language. In these…

An ELT's Solution to Combat Plagiarism: "Birth" of CALL.

Science.gov (United States)

Sabieh, Christine

One English-as-a Second-Language professor fought plagiarism using computer assisted language learning (CALL). She succeeded in getting half of her class to write documented research papers free of plagiarism. Although all of the students claimed to know how to avoid plagiarizing, 35 percent presented the work with minor traces of plagiarism. The…

Capitalizing on Speaking Skill of EFL Learners for the Language Literacy

OpenAIRE

Fauzia Hasan Siddiqui

2014-01-01

This study aims at grabbing the attention of EFL /ESL teachers, trainers, and administrators towards the importance of teaching speaking skill to enhance overall language proficiency of EFL learners. Comprehensive research done in the field of applied linguistics and English Language Teaching (ELT) establishes a positive correlation of speaking skill with the overall language proficiency. Despite this obvious significance of speaking skill in language learning process, it has not gained suffi...

How to describe grammar and vocabulary in ELT

CERN Document Server

Liu, Dilin

2013-01-01

Language description plays an important role in language learning/teaching because it often determines what specific language forms, features, and usages are taught and how. A good understanding of language description is vital for language teachers and material writers and should constitute an important part of their knowledge. This book provides a balanced treatment of both theory and practice. It focuses on some of the most important and challenging grammar and vocabulary usage questions. Using these questions as examples, it shows how theory can inform practice and how grammar and vocab

Comparison of 3 tests to detect acaricide resistance in Boophilus decoloratus on dairy farms in the Eastern Cape Province, South Africa

Directory of Open Access Journals (Sweden)

S. Mekonnen

2003-06-01

Full Text Available The susceptibility of the larval offspring of engorged female Boophilus decoloratus, and of the engorged females, collected from cattle on the dairy farms Brycedale, Sunny Grove and Welgevind in the Eastern Cape Province, South Africa, was tested against the acaricides amitraz, chlorfenvinphos and cypermethrin. Resistance was determined by means of the Shaw Larval Immersion Test (SLIT for larvae and the Reproductive Estimate Test (RET and Egg Laying Test (ELT for adults. At Brycedale the tests all indicated resistance to chlorfenvinphos, and RET and ELT indicated resistance to amitraz and emerging resistance to cypermethrin. At Sunny Grove, B. decoloratus was resistant to cypermethrin using SLIT and exhibited emerging resistance to chlorfenvinphos with SLIT and to cypermethrin with both RET and ELT. At Welgevind, resistance was recorded against chlorfenvinphos (SLIT and against cypermethrin (ELT, and emerging resistance against permethrin (RET. The results obtained with RET and ELT were generally comparable, but often differed from those obtained with SLIT. Resistance could be detected within 7 days with ELT compared to 42 days with RET and 60 days with SLIT.

A deep learning framework for financial time series using stacked autoencoders and long-short term memory

Science.gov (United States)

Bao, Wei; Rao, Yulei

2017-01-01

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day’s closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance. PMID:28708865

A deep learning framework for financial time series using stacked autoencoders and long-short term memory.

Directory of Open Access Journals (Sweden)

Wei Bao

Full Text Available The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT, stacked autoencoders (SAEs and long-short term memory (LSTM are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock price forecasting for the first time. The deep learning framework comprises three stages. First, the stock price time series is decomposed by WT to eliminate noise. Second, SAEs is applied to generate deep high-level features for predicting the stock price. Third, high-level denoising features are fed into LSTM to forecast the next day's closing price. Six market indices and their corresponding index futures are chosen to examine the performance of the proposed model. Results show that the proposed model outperforms other similar models in both predictive accuracy and profitability performance.

Adjustment to subtle time constraints and power law learning in rapid serial visual presentation

Directory of Open Access Journals (Sweden)

Jacqueline Chakyung Shin

2015-11-01

Full Text Available We investigated whether attention could be modulated through the implicit learning of temporal information in a rapid serial visual presentation (RSVP task. Participants identified two target letters among numeral distractors. The stimulus-onset asynchrony immediately following the first target (SOA1 varied at three levels (70, 98, and 126 ms randomly between trials or fixed within blocks of trials. Practice over three consecutive days resulted in a continuous improvement in the identification rate for both targets and attenuation of the attentional blink (AB, a decrement in target (T2 identification when presented 200-400 ms after another target (T1. Blocked SOA1s led to a faster rate of improvement in RSVP performance and more target order reversals relative to random SOA1s, suggesting that the implicit learning of SOA1 positively affected performance. The results also reveal power law learning curves for individual target identification as well as the reduction in the AB decrement. These learning curves reflect the spontaneous emergence of skill through subtle attentional modulations rather than general attentional distribution. Together, the results indicate that implicit temporal learning could improve high level and rapid cognitive processing and highlights the sensitivity and adaptability of the attentional system to subtle constraints in stimulus timing.

Interview with Alan Maley on Teaching and Learning Creative Writing

OpenAIRE

Ruzbeh Babaee

2015-01-01

Alan Maley is a British, award-winning, internationally-known writer and artist, highly regarded for his unique observation of life at the turn of the century. He has been involved in English Language Teaching (ELT) for over 50 years. He worked for the British Council in Yugoslavia, Ghana, Italy, France, China and India and was the Director of the Bell Educational Trust in Cambridge for 5 years. He later worked in universities in Singapore, Thailand, Malaysia and UK. Alan has published over 4...

Predicting the time of conversion to MCI in the elderly: role of verbal expression and learning.

Science.gov (United States)

Oulhaj, Abderrahim; Wilcock, Gordon K; Smith, A David; de Jager, Celeste A

2009-11-03

Increasing awareness that minimal or mild cognitive impairment (MCI) in the elderly may be a precursor of dementia has led to an increase in the number of people attending memory clinics. We aimed to develop a way of predicting the period of time before cognitive impairment occurs in community-dwelling elderly. The method is illustrated by the use of simple tests of different cognitive domains. A cohort of 241 normal elderly volunteers was followed for up to 20 years with regular assessments of cognitive abilities using the Cambridge Cognitive Examination (CAMCOG); 91 participants developed MCI. We used interval-censored survival analysis statistical methods to model which baseline cognitive tests best predicted the time to convert to MCI. Out of several baseline variables, only age and CAMCOG subscores for expression and learning/memory were predictors of the time to conversion. The time to conversion was 14% shorter for each 5 years of age, 17% shorter for each point lower in the expression score, and 15% shorter for each point lower in the learning score. We present in tabular form the probability of converting to MCI over intervals between 2 and 10 years for different combinations of expression and learning scores. In apparently normal elderly people, subtle measurable cognitive deficits that occur within the normal range on standard testing protocols reliably predict the time to clinically relevant cognitive impairment long before clinical symptoms are reported.

A. S. Hornby and 50 Years of the Hornby Trust

Science.gov (United States)

Smith, Richard; Bowers, Roger

2012-01-01

A. S. Hornby can justly be considered the "father" of UK-based ELT. He was the founder and first Editor of English Language Teaching (now known as ELT Journal); he established the ground rules for situational language teaching, the dominant ELT methodology in the United Kingdom up until the 1970s; he was the chief originator of the…

Reducing adaptive optics latency using Xeon Phi many-core processors

Science.gov (United States)

Barr, David; Basden, Alastair; Dipper, Nigel; Schwartz, Noah

2015-11-01

The next generation of Extremely Large Telescopes (ELTs) for astronomy will rely heavily on the performance of their adaptive optics (AO) systems. Real-time control is at the heart of the critical technologies that will enable telescopes to deliver the best possible science and will require a very significant extrapolation from current AO hardware existing for 4-10 m telescopes. Investigating novel real-time computing architectures and testing their eligibility against anticipated challenges is one of the main priorities of technology development for the ELTs. This paper investigates the suitability of the Intel Xeon Phi, which is a commercial off-the-shelf hardware accelerator. We focus on wavefront reconstruction performance, implementing a straightforward matrix-vector multiplication (MVM) algorithm. We present benchmarking results of the Xeon Phi on a real-time Linux platform, both as a standalone processor and integrated into an existing real-time controller (RTC). Performance of single and multiple Xeon Phis are investigated. We show that this technology has the potential of greatly reducing the mean latency and variations in execution time (jitter) of large AO systems. We present both a detailed performance analysis of the Xeon Phi for a typical E-ELT first-light instrument along with a more general approach that enables us to extend to any AO system size. We show that systematic and detailed performance analysis is an essential part of testing novel real-time control hardware to guarantee optimal science results.

Sleep parameters, functional status and time post-stroke are associated with off-line motor skill learning in people with chronic stroke

Directory of Open Access Journals (Sweden)

Catherine eSiengsukon

2015-10-01

Full Text Available Background: Mounting evidence demonstrates that individuals with stroke benefit from sleep to enhance learning of a motor task. While stage NREM2 sleep and REM sleep have been associated with off-line motor skill learning in neurologically-intact individuals, it remains unknown which sleep parameters or specific sleep stages are associated with off-line motor skill learning in individuals with stroke. Methods: Twenty individuals with chronic stroke (> 6 months following stroke and 10 neurologically slept for three consecutive nights in a sleep laboratory with polysomnography. Participants practiced a tracking task the morning before the third night and underwent a retention test the morning following the third night. Off-line learning on the tracking task was assessed. Pearson’s correlations assessed for associations between the magnitude of off-line learning and sleep variables, age, upper extremity motor function, stroke severity, depression and time since stroke occurrence.Results: Individuals with stroke performed with significantly less error on the tracking task following a night of sleep (p=.006 while the control participants did not (p=.816. Increased sleep efficiency (r= -.285, less time spent in stage NREM3 sleep (r=.260, and more time spent in stage REM sleep (r= -.266 was weakly-to-moderately associated with increased magnitude of off-line motor learning. Furthermore, higher upper-extremity motor function (r = -.400, lower stroke severity (r = .360, and less time since stroke occurrence (r=.311 were moderately associated with increased magnitude of off-line motor learning. Conclusion: This study is the first study to provide insight into which sleep stages and individual characteristics may be associated with off-line learning in people with stroke. Future work should continue to understand which factors or combination of factors promote off-line motor learning in people with neurologic injury to best promote motor recovery in

Cerebral activation related to implicit sequence learning in a Double Serial Reaction Time task

NARCIS (Netherlands)

van der Graaf, FHCE; Maguire, RP; Leenders, KL; de Jong, BM

2006-01-01

Using functional magnetic resonance imaging (fMRI), we examined the distribution of cerebral activations related to implicitly learning a series of fixed stimulus-response combinations. In a novel - bimanual - variant of the Serial Reaction Time task (SRT), simultaneous finger movements of the two

Using American Coming-of-Age Stories in the ELT Classroom

Directory of Open Access Journals (Sweden)

Elena Ortells Montón

2017-05-01

Full Text Available Reading constitutes solid grounds for the development of basic language and critical skills as well as for the improvement of Intercultural Communicative Competence. However, in a world dominated by visual media and technology, getting young people to read becomes a challenging experience, which turns out to be even more problematic in English language teaching. Young adult literature and multicultural coming-of-age stories can offer teachers the necessary materials to foster interest in reading and to raise intercultural awareness. In spite of its limited scope, the project reported in this article proved that a conscientious choice of extracts taken from Yang’s American Born Chinese, Alexie’s The Absolutely True Diary of a Part-Time Indian, Cisneros’s The House on Mango Street and Morrison’s The Bluest Eye, among others, could contribute to improving language learners’ linguistic and sociocultural competence. The project employed an interactive methodology based on a combination of critical multicultural pedagogy and reader-response theory, centering on the students’ perspectives of their learning experience. While this experience did not answer the question whether the learners’ reading competence had in fact increased, the students themselves acknowledged a substantial increase in reading motivation and confidence as well as cultural awareness.

Distributed Open and Distance Learning: How Does E-Learning Fit? LSDA Reports.

Science.gov (United States)

Fletcher, Mick

The distinctions between types of open and distance learning broadly equate to the concept of learning at a time, place, and pace that best suits the learner. Distance learning refers to geography, whereas open learning refers to time. Flexible learning is a generic term referring either to geography or time. Combining these distinctions allows…

Sci-Fri AM: Quality, Safety, and Professional Issues 04: Predicting waiting times in Radiation Oncology using machine learning

International Nuclear Information System (INIS)

Joseph, Ackeem; Herrera, David; Hijal, Tarek; Hendren, Laurie; Leung, Alvin; Wainberg, Justin; Sawaf, Marya; Maxim, Gorshkov; Maglieri, Robert; Keshavarz, Mehryar; Kildea, John

2016-01-01

We describe a method for predicting waiting times in radiation oncology. Machine learning is a powerful predictive modelling tool that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The patient waiting experience remains one of the most vexing challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick and in pain, to worry about when they will receive the care they need. In radiation oncology, patients typically experience three types of waiting: Waiting at home for their treatment plan to be prepared Waiting in the waiting room for daily radiotherapy Waiting in the waiting room to see a physician in consultation or follow-up These waiting periods are difficult for staff to predict and only rough estimates are typically provided, based on personal experience. In the present era of electronic health records, waiting times need not be so uncertain. At our centre, we have incorporated the electronic treatment records of all previously-treated patients into our machine learning model. We found that the Random Forest Regression model provides the best predictions for daily radiotherapy treatment waiting times (type 2). Using this model, we achieved a median residual (actual minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. The main features that generated the best fit model (from most to least significant) are: Allocated time, median past duration, fraction number and the number of treatment fields.

Sci-Fri AM: Quality, Safety, and Professional Issues 04: Predicting waiting times in Radiation Oncology using machine learning

Energy Technology Data Exchange (ETDEWEB)

Joseph, Ackeem; Herrera, David; Hijal, Tarek; Hendren, Laurie; Leung, Alvin; Wainberg, Justin; Sawaf, Marya; Maxim, Gorshkov; Maglieri, Robert; Keshavarz, Mehryar; Kildea, John [McGill University Health Centre (Canada)

2016-08-15

We describe a method for predicting waiting times in radiation oncology. Machine learning is a powerful predictive modelling tool that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The patient waiting experience remains one of the most vexing challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick and in pain, to worry about when they will receive the care they need. In radiation oncology, patients typically experience three types of waiting: Waiting at home for their treatment plan to be prepared Waiting in the waiting room for daily radiotherapy Waiting in the waiting room to see a physician in consultation or follow-up These waiting periods are difficult for staff to predict and only rough estimates are typically provided, based on personal experience. In the present era of electronic health records, waiting times need not be so uncertain. At our centre, we have incorporated the electronic treatment records of all previously-treated patients into our machine learning model. We found that the Random Forest Regression model provides the best predictions for daily radiotherapy treatment waiting times (type 2). Using this model, we achieved a median residual (actual minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. The main features that generated the best fit model (from most to least significant) are: Allocated time, median past duration, fraction number and the number of treatment fields.

A matter of timing: harm reduction in learned helplessness.

Science.gov (United States)

Richter, Sophie Helene; Sartorius, Alexander; Gass, Peter; Vollmayr, Barbara

2014-11-03

Learned helplessness has excellent validity as an animal model for depression, but problems in reproducibility limit its use and the high degree of stress involved in the paradigm raises ethical concerns. We therefore aimed to identify which and how many trials of the learned helplessness paradigm are necessary to distinguish between helpless and non-helpless rats. A trial-by-trial reanalysis of tests from 163 rats with congenital learned helplessness or congenital non-learned helplessness and comparison of 82 rats exposed to inescapable shock with 38 shock-controls revealed that neither the first test trials, when rats showed unspecific hyperlocomotion, nor trials of the last third of the test, when almost all animals responded quickly to the stressor, contributed to sensitivity and specificity of the test. Considering only trials 3-10 improved the classification of helpless and non-helpless rats. The refined analysis allows abbreviation of the test for learned helplessness from 15 trials to 10 trials thereby reducing pain and stress of the experimental animals without losing statistical power.

Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics

Science.gov (United States)

Wehmeyer, Christoph; Noé, Frank

2018-06-01

Inspired by the success of deep learning techniques in the physical and chemical sciences, we apply a modification of an autoencoder type deep neural network to the task of dimension reduction of molecular dynamics data. We can show that our time-lagged autoencoder reliably finds low-dimensional embeddings for high-dimensional feature spaces which capture the slow dynamics of the underlying stochastic processes—beyond the capabilities of linear dimension reduction techniques.

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

Science.gov (United States)

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.

Science.gov (United States)

Wei, Qinglai; Li, Benkai; Song, Ruizhuo

2018-04-01

In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.

Optimal and Scalable Caching for 5G Using Reinforcement Learning of Space-Time Popularities

Science.gov (United States)

Sadeghi, Alireza; Sheikholeslami, Fatemeh; Giannakis, Georgios B.

2018-02-01

Small basestations (SBs) equipped with caching units have potential to handle the unprecedented demand growth in heterogeneous networks. Through low-rate, backhaul connections with the backbone, SBs can prefetch popular files during off-peak traffic hours, and service them to the edge at peak periods. To intelligently prefetch, each SB must learn what and when to cache, while taking into account SB memory limitations, the massive number of available contents, the unknown popularity profiles, as well as the space-time popularity dynamics of user file requests. In this work, local and global Markov processes model user requests, and a reinforcement learning (RL) framework is put forth for finding the optimal caching policy when the transition probabilities involved are unknown. Joint consideration of global and local popularity demands along with cache-refreshing costs allow for a simple, yet practical asynchronous caching approach. The novel RL-based caching relies on a Q-learning algorithm to implement the optimal policy in an online fashion, thus enabling the cache control unit at the SB to learn, track, and possibly adapt to the underlying dynamics. To endow the algorithm with scalability, a linear function approximation of the proposed Q-learning scheme is introduced, offering faster convergence as well as reduced complexity and memory requirements. Numerical tests corroborate the merits of the proposed approach in various realistic settings.

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

Science.gov (United States)

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of Stand-Alone Displays for Time Management in a Creativity-Driven Learning Environment

DEFF Research Database (Denmark)

Frimodt-Møller, Søren

2017-01-01

This paper considers the pros and cons of stand-alone displays, analog (e.g. billboards, blackboards, whiteboards, large pieces of paper etc.) as well as digital (e.g. large shared screens, digital whiteboards or similar), as tools for time management processes in a creativity-driven learning...

Uncertainties in global radiation time series forecasting using machine learning: The multilayer perceptron case

International Nuclear Information System (INIS)

Voyant, Cyril; Notton, Gilles; Darras, Christophe; Fouilloy, Alexis; Motte, Fabrice

2017-01-01

As global solar radiation forecasting is a very important challenge, several methods are devoted to this goal with different levels of accuracy and confidence. In this study we propose to better understand how the uncertainty is propagated in the context of global radiation time series forecasting using machine learning. Indeed we propose to decompose the error considering four kinds of uncertainties: the error due to the measurement, the variability of time series, the machine learning uncertainty and the error related to the horizon. All these components of the error allow to determinate a global uncertainty generating prediction bands related to the prediction efficiency. We also have defined a reliability index which could be very interesting for the grid manager in order to estimate the validity of predictions. We have experimented this method on a multilayer perceptron which is a popular machine learning technique. We have shown that the global error and its components are essential to quantify in order to estimate the reliability of the model outputs. The described method has been successfully applied to four meteorological stations in Mediterranean area. - Highlights: • Solar irradiation predictions require confidence bands. • There are a lot of kinds of uncertainties to take into account in order to propose prediction bands. • the ranking of different kinds of uncertainties is essential to propose an operational tool for the grid managers.

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

Science.gov (United States)

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

2015-01-01

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

Time-Contrastive Learning Based DNN Bottleneck Features for Text-Dependent Speaker Verification

DEFF Research Database (Denmark)

Sarkar, Achintya Kumar; Tan, Zheng-Hua

2017-01-01

In this paper, we present a time-contrastive learning (TCL) based bottleneck (BN) feature extraction method for speech signals with an application to text-dependent (TD) speaker verification (SV). It is well-known that speech signals exhibit quasi-stationary behavior in and only in a short interval......, and the TCL method aims to exploit this temporal structure. More specifically, it trains deep neural networks (DNNs) to discriminate temporal events obtained by uniformly segmenting speech signals, in contrast to existing DNN based BN feature extraction methods that train DNNs using labeled data...... to discriminate speakers or pass-phrases or phones or a combination of them. In the context of speaker verification, speech data of fixed pass-phrases are used for TCL-BN training, while the pass-phrases used for TCL-BN training are excluded from being used for SV, so that the learned features can be considered...

Evaluation of Online Log Variables That Estimate Learners' Time Management in a Korean Online Learning Context

Science.gov (United States)

Jo, Il-Hyun; Park, Yeonjeong; Yoon, Meehyun; Sung, Hanall

2016-01-01

The purpose of this study was to identify the relationship between the psychological variables and online behavioral patterns of students, collected through a learning management system (LMS). As the psychological variable, time and study environment management (TSEM), one of the sub-constructs of MSLQ, was chosen to verify a set of time-related…

Ecologia: The Assumptions, Expectations, and Strategies of Modern Language Students Working in a Self-Access Learning Environment for the First Time.

Science.gov (United States)

Piper, Alison

1994-01-01

This study examined 29 second-year undergraduate students of Spanish using a self-access learning environment for the first time, focusing on their language attitudes and learning strategies. The results show that, even as modern languages majors, the students possessed a model of language and strategies for learning that were significantly…

On the best learning algorithm for web services response time prediction

DEFF Research Database (Denmark)

Madsen, Henrik; Albu, Razvan-Daniel; Popentiu-Vladicescu, Florin

2013-01-01

In this article we will examine the effect of different learning algorithms, while training the MLP (Multilayer Perceptron) with the intention of predicting web services response time. Web services do not necessitate a user interface. This may seem contradictory to most people's concept of what...... an application is. A Web service is better imagined as an application "segment," or better as a program enabler. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the response of web services during their operation is very important....

Using machine learning to identify structural breaks in single-group interrupted time series designs.

Science.gov (United States)

Linden, Ariel; Yarnold, Paul R

2016-12-01

Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

Part-Time Community College Instructors Teaching in Learning Communities: An Exploratory Multiple Case Study

Science.gov (United States)

Paterson, John W.

2017-01-01

Community colleges have a greater portion of students at-risk for college completion than four-year schools and faculty at these institutions are overwhelmingly and increasingly part-time. Learning communities have been identified as a high-impact practice with numerous benefits documented for community college instructors and students: a primary…

Perceived Learning and Timely Graduation for Business Undergraduates Taking an Online or Hybrid Course

Science.gov (United States)

Blau, Gary; Drennan, Rob B.; Hochner, Arthur; Kapanjie, Darin

2016-01-01

An online survey tested the impact of background, technological, and course-related variables on perceived learning and timely graduation for a complete data sample of 263 business undergraduates taking at least one online or hybrid course in the fall of 2015. Hierarchical regression results showed that course-related variables (instructor…

Distributed Cerebellar Motor Learning; a Spike-Timing-Dependent Plasticity Model

Directory of Open Access Journals (Sweden)

Niceto Rafael Luque

2016-03-01

Full Text Available Deep cerebellar nuclei neurons receive both inhibitory (GABAergic synaptic currents from Purkinje cells (within the cerebellar cortex and excitatory (glutamatergic synaptic currents from mossy fibres. Those two deep cerebellar nucleus inputs are thought to be also adaptive, embedding interesting properties in the framework of accurate movements. We show that distributed spike-timing-dependent plasticity mechanisms (STDP located at different cerebellar sites (parallel fibres to Purkinje cells, mossy fibres to deep cerebellar nucleus cells, and Purkinje cells to deep cerebellar nucleus cells in close-loop simulations provide an explanation for the complex learning properties of the cerebellum in motor learning. Concretely, we propose a new mechanistic cerebellar spiking model. In this new model, deep cerebellar nuclei embed a dual functionality: deep cerebellar nuclei acting as a gain adaptation mechanism and as a facilitator for the slow memory consolidation at mossy fibres to deep cerebellar nucleus synapses. Equipping the cerebellum with excitatory (e-STDP and inhibitory (i-STDP mechanisms at deep cerebellar nuclei afferents allows the accommodation of synaptic memories that were formed at parallel fibres to Purkinje cells synapses and then transferred to mossy fibres to deep cerebellar nucleus synapses. These adaptive mechanisms also contribute to modulate the deep-cerebellar-nucleus-output firing rate (output gain modulation towards optimising its working range.

Unsupervised learning by spike timing dependent plasticity in phase change memory (PCM synapses

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Stefano eAmbrogio

2016-03-01

Full Text Available We present a novel one-transistor/one-resistor (1T1R synapse for neuromorphic networks, based on phase change memory (PCM technology. The synapse is capable of spike-timing dependent plasticity (STDP, where gradual potentiation relies on set transition, namely crystallization, in the PCM, while depression is achieved via reset or amorphization of a chalcogenide active volume. STDP characteristics are demonstrated by experiments under variable initial conditions and number of pulses. Finally, we support the applicability of the 1T1R synapse for learning and recognition of visual patterns by simulations of fully connected neuromorphic networks with 2 or 3 layers with high recognition efficiency. The proposed scheme provides a feasible low-power solution for on-line unsupervised machine learning in smart reconfigurable sensors.

Statistical Learning and Adaptive Decision-Making Underlie Human Response Time Variability in Inhibitory Control

Directory of Open Access Journals (Sweden)

Ning eMa

2015-08-01

Full Text Available Response time (RT is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task, in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop, and stop-signal onset time, SSD (stop-signal delay, with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop and SSD. The human behavioral data (n=20 bear out this prediction, showing P(stop and SSD both to be significant, independent predictors of RT, with P(stop being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

Statistical learning and adaptive decision-making underlie human response time variability in inhibitory control.

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Ma, Ning; Yu, Angela J

2015-01-01

Response time (RT) is an oft-reported behavioral measure in psychological and neurocognitive experiments, but the high level of observed trial-to-trial variability in this measure has often limited its usefulness. Here, we combine computational modeling and psychophysics to examine the hypothesis that fluctuations in this noisy measure reflect dynamic computations in human statistical learning and corresponding cognitive adjustments. We present data from the stop-signal task (SST), in which subjects respond to a go stimulus on each trial, unless instructed not to by a subsequent, infrequently presented stop signal. We model across-trial learning of stop signal frequency, P(stop), and stop-signal onset time, SSD (stop-signal delay), with a Bayesian hidden Markov model, and within-trial decision-making with an optimal stochastic control model. The combined model predicts that RT should increase with both expected P(stop) and SSD. The human behavioral data (n = 20) bear out this prediction, showing P(stop) and SSD both to be significant, independent predictors of RT, with P(stop) being a more prominent predictor in 75% of the subjects, and SSD being more prominent in the remaining 25%. The results demonstrate that humans indeed readily internalize environmental statistics and adjust their cognitive/behavioral strategy accordingly, and that subtle patterns in RT variability can serve as a valuable tool for validating models of statistical learning and decision-making. More broadly, the modeling tools presented in this work can be generalized to a large body of behavioral paradigms, in order to extract insights about cognitive and neural processing from apparently quite noisy behavioral measures. We also discuss how this behaviorally validated model can then be used to conduct model-based analysis of neural data, in order to help identify specific brain areas for representing and encoding key computational quantities in learning and decision-making.

Off-Policy Reinforcement Learning: Optimal Operational Control for Two-Time-Scale Industrial Processes.

Science.gov (United States)

Li, Jinna; Kiumarsi, Bahare; Chai, Tianyou; Lewis, Frank L; Fan, Jialu

2017-12-01

Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.

Mental Time Travel, Memory and the Social Learning Strategies Tournament

Science.gov (United States)

Fogarty, L.; Rendell, L.; Laland, K. N.

2012-01-01

The social learning strategies tournament was an open computer-based tournament investigating the best way to learn in a changing environment. Here we present an analysis of the impact of memory on the ability of strategies entered into the social learning strategies tournament (Rendell, Boyd, et al., 2010) to modify their own behavior to suit a…

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task.

Directory of Open Access Journals (Sweden)

Pavel Sanda

2017-09-01

Full Text Available Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making.

Technology Applied to ELT: Reviewing Practical Uses to Enhance English Teaching Programs

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Javier Rojas Serrano

2007-12-01

Full Text Available In this paper, the author reports on some of the areas of technology currently used in the teaching and learning of languages, and reviews some of the uses of technological tools that are present in the English Adult Program and activities carried out at The Centro Colombo Americano (CCA in Bogota, Colombia. After briefly describing what is being applied worldwide in terms of what is being done at the CCA, some suggestions are offered in order to enhance the English teaching and learning processes through the use of new technologies.

Age and time effects on implicit and explicit learning

NARCIS (Netherlands)

Verneau, M.; Kamp, J. van der; Savelsbergh, G.J.P.; Looze, M.P. de

2014-01-01

Study Context: It has been proposed that effects of aging are more pronounced for explicit than for implicit motor learning. The authors evaluated this claim by comparing the efficacy of explicit and implicit learning of a movement sequence in young and older adults, and by testing the resilience

Age and Time Effects on Implicit and Explicit Learning

NARCIS (Netherlands)

Verneau, M.M.N.; van der Kamp, J.; Savelsbergh, G.J.P.; de Looze, M.P.

2014-01-01

Study Context: It has been proposed that effects of aging are more pronounced for explicit than for implicit motor learning. The authors evaluated this claim by comparing the efficacy of explicit and implicit learning of a movement sequence in young and older adults, and by testing the resilience

An Effective Role of E-Learning Technology For English Language Teaching By Using Meta Communication Actors

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Ilknur ISTIFCI

2011-10-01

Full Text Available Meta communication plays a key role in foreign language learning and teaching. Broadly speaking, meta communication is communication about communication. Meta communication is something that goes beyond communication and all language learners and teachers should be familiar with its existence. It should be stressed that meta communication which accompanies any message is very powerful. In face to face writing lessons, the student can make emphasis on any point by utilizing larger fonts, capital letters, or bold fonts in his essay. However, in virtual learning environments, students can make use of emoticons like :- “happy”, :-( “sad”, :-/ “perplexed”, O.o “confused” to communicate about communication. Further, they can deploy some acronyms like (BTW= By the way, ASAP= as soon as possible, TM= tomorrow to easily convey their messages. It should be emphasized that E-learning applications (virtual worlds, second life, ICTs are very beneficial in foreign language learning and teaching since they create a platform for students and teachers to interact in a context with no boundaries of time and distance. In Transformational Generative Grammar, foreign language teachers describe syntactic structures in English by using grammatical symbols with meta communicational elements. For instance, every English Foreign Language-EFL or English Language Teaching-ELT teachers or students is familiar with the symbols and related meanings like (S= sentence, subject, V= verb, O= object, N= noun, NP= noun phrase, VP= verb phrase, etc.. On the other side, when teaching English pronunciation to Turkish EFL learners, foreign language teachers utilize phonetic symbols like /è, æ, å, ğ, w, ŋ/ to write transcriptions of English words. These phonetic symbols have meta communicational elements in their composition because they communicate about communication. At this juncture, foreign language teachers should learn frequently used emoticons, keyboard

Analysed potential of big data and supervised machine learning techniques in effectively forecasting travel times from fused data

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Ivana Šemanjski

2015-12-01

Full Text Available Travel time forecasting is an interesting topic for many ITS services. Increased availability of data collection sensors increases the availability of the predictor variables but also highlights the high processing issues related to this big data availability. In this paper we aimed to analyse the potential of big data and supervised machine learning techniques in effectively forecasting travel times. For this purpose we used fused data from three data sources (Global Positioning System vehicles tracks, road network infrastructure data and meteorological data and four machine learning techniques (k-nearest neighbours, support vector machines, boosting trees and random forest. To evaluate the forecasting results we compared them in-between different road classes in the context of absolute values, measured in minutes, and the mean squared percentage error. For the road classes with the high average speed and long road segments, machine learning techniques forecasted travel times with small relative error, while for the road classes with the small average speeds and segment lengths this was a more demanding task. All three data sources were proven itself to have a high impact on the travel time forecast accuracy and the best results (taking into account all road classes were achieved for the k-nearest neighbours and random forest techniques.

Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics

Science.gov (United States)

Yu, Tao; Cai, Weiwei; Liu, Yingzheng

2018-04-01

Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions. Extreme learning machine is cited here as an example for demonstrative purpose simply due to its ease of implementation, fast learning speed, and good generalization performance. Extensive numerical studies were performed, and the results show that the new method can dramatically reduce the computational time compared with the classical iterative methods. This technique is expected to be an alternative to existing methods when sufficient training data are available. Although this work is discussed under the context of tomographic absorption spectroscopy, we expect it to be useful also to other high speed tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence which have been demonstrated for combustion diagnostics.

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

International Nuclear Information System (INIS)

Veronesi, F; Grassi, S

2016-01-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners. (paper)

Generation and Validation of Spatial Distribution of Hourly Wind Speed Time-Series using Machine Learning

Science.gov (United States)

Veronesi, F.; Grassi, S.

2016-09-01

Wind resource assessment is a key aspect of wind farm planning since it allows to estimate the long term electricity production. Moreover, wind speed time-series at high resolution are helpful to estimate the temporal changes of the electricity generation and indispensable to design stand-alone systems, which are affected by the mismatch of supply and demand. In this work, we present a new generalized statistical methodology to generate the spatial distribution of wind speed time-series, using Switzerland as a case study. This research is based upon a machine learning model and demonstrates that statistical wind resource assessment can successfully be used for estimating wind speed time-series. In fact, this method is able to obtain reliable wind speed estimates and propagate all the sources of uncertainty (from the measurements to the mapping process) in an efficient way, i.e. minimizing computational time and load. This allows not only an accurate estimation, but the creation of precise confidence intervals to map the stochasticity of the wind resource for a particular site. The validation shows that machine learning can minimize the bias of the wind speed hourly estimates. Moreover, for each mapped location this method delivers not only the mean wind speed, but also its confidence interval, which are crucial data for planners.

Calculation of upper esophageal sphincter restitution time from high resolution manometry data using machine learning.

Science.gov (United States)

Jungheim, Michael; Busche, Andre; Miller, Simone; Schilling, Nicolas; Schmidt-Thieme, Lars; Ptok, Martin

2016-10-15

After swallowing, the upper esophageal sphincter (UES) needs a certain amount of time to return from maximum pressure to the resting condition. Disturbances of sphincter function not only during the swallowing process but also in this phase of pressure restitution may lead to globus sensation or dysphagia. Since UES pressures do not decrease in a linear or asymptotic manner, it is difficult to determine the exact time when the resting pressure is reached, even when using high resolution manometry (HRM). To overcome this problem a Machine Learning model was established to objectively determine the UES restitution time (RT) and moreover to collect physiological data on sphincter function after swallowing. HRM-data of 15 healthy participants performing 10 swallows each were included. After manual annotation of the RT interval by two swallowing experts, data were transferred to the Machine Learning model, which applied a sequence labeling modeling approach based on logistic regression to learn and objectivize the characteristics of all swallows. Individually computed RT values were then compared with the annotated values. Estimates of the RT were generated by the Machine Learning model for all 150 swallows. When annotated by swallowing experts mean RT of 11.16s±5.7 (SD) and 10.04s±5.74 were determined respectively, compared to model-generated values from 8.91s±3.71 to 10.87s±4.68 depending on model selection. The correlation score for the annotated RT of both examiners was 0.76 and 0.63 to 0.68 for comparison of model predicted values. Restitution time represents an important physiologic swallowing parameter not previously considered in HRM-studies of the UES, especially since disturbances of UES restitution may increase the risk of aspiration. The data presented here show that it takes approximately 9 to 11s for the UES to come to rest after swallowing. Based on maximal RT values, we demonstrate that an interval of 25-30s in between swallows is necessary until the

Project Management in Real Time: A Service-Learning Project

Science.gov (United States)

Larson, Erik; Drexler, John A., Jr.

2010-01-01

This article describes a service-learning assignment for a project management course. It is designed to facilitate hands-on student learning of both the technical and the interpersonal aspects of project management, and it involves student engagement with real customers and real stakeholders in the creation of real events with real outcomes. As…

Devoloping an integrated analysis approach to exoplanetary spectroscopy

Science.gov (United States)

Waldmann, Ingo

2015-07-01

Analysing the atmospheres of Earth and SuperEarth type planets for possible biomarkers will push us to the limits of current and future instrumentation. As the field matures, we must also upgrade our data analysis and interpretation techniques from their "ad-hoc" beginnings to a solid statistical foundation. This is particularly important for the optimal exploitation of future instruments, such as JWST and E-ELT. At the limits of low signal-to-noise, we are prone to two sources of biases: 1) Prior selection in the data reduction; 2) Prior constraints on the spectral retrieval. A unified set of tools addressing both points is required. To de-trend low S/N, correlated data, we demonstrated blind-source-separation (BSS) machine learning techniques to be a significant step forward. Both in photometry and spectroscopy. BSS finds applications in fields as diverse as medical imaging to cosmology. Applied to exoplanets, it allows us to resolve de-trending biases and demonstrate consistency between data sets that were previously found to be highly discrepant and subject to much debate. For the interpretation of the data, we developed a novel atmospheric retrieval suite, Tau-REx. Tau-REx implements an unbiased prior selections via a custom built pattern recognition software. A full subsequent mapping of the likelihood space (using cluster computing) allows us, for the first time, to fully study degeneracies and biases in emission and transmission spectroscopy. The development of a coherent end-to-end infrastructure is paramount to the characterisation of ever smaller and fainter foreign worlds. In this conference, I will discuss what we have learned for current observations and the need for unified statistical frameworks in the era of JWST, E-ELT.

MECAR (Main Ring Excitation Controller and Regulator): A real time learning regulator for the Fermilab Main Ring or the Main Injector synchrotron

International Nuclear Information System (INIS)

Flora, R.; Martin, K.; Moibenko, A.; Pfeffer, H.; Wolff, D.; Prieto, P.; Hays, S.

1995-04-01

The real time computer for controlling and regulating the FNAL Main Ring power supplies has been upgraded with a new learning control system. The learning time of the system has been reduced by an order of magnitude, mostly through the implementation of a 95 tap FIR filter in the learning algorithm. The magnet system consists of three buses, which must track each other during a ramp from 100 to 1700 amps at a 2.4 second repetition rate. This paper will present the system configuration and the tools used during development and testing

Developing Mentors: Adult participation, practices, and learning in an out-of-school time STEM program

Science.gov (United States)

Scipio, Deana Aeolani

This dissertation examines learning within an out-of-school time (OST) Science, Technology, Engineering, and Mathematics (STEM) broadening participation program. The dissertation includes an introduction, three empirical chapters (written as individual articles), and a conclusion. The dissertation context is a chemical oceanography OST program for middle school students called Project COOL---Chemical Oceanography Outside the Lab. The program was a collaboration between middle school OST programming, a learning sciences research laboratory, and a chemical oceanography laboratory. Both labs were located at a research-based university in the Pacific Northwest of the United States. Participants include 34 youth, 12 undergraduates, and five professional scientists. The dissertation data corpus includes six years of ethnographic field notes across three field sites, 400 hours of video and audio recordings, 40 hours of semi-structured interviews, and more than 100 participant generated artifacts. Analysis methods include comparative case analysis, cognitive mapping, semiotic cluster analysis, video interaction analysis, and discourse analysis. The first empirical article focuses on synthesizing productive programmatic features from four years of design-based research.. The second article is a comparative case study of three STEM mentors from non-dominant communities in the 2011 COOL OST Program. The third article is a comparative case study of undergraduates learning to be mentors in the 2014 COOL OST Program. Findings introduce Deep Hanging as a theory of learning in practice. Deep Hanging entails authentic tasks in rich contexts, providing access, capitalizing on opportunity, and building interpersonal relationships. Taken together, these three chapters illuminate the process of designing a rich OST learning environment and the kinds of learning in practice that occurred for adult learners learning to be mentors through their participation in the COOL OST program. In

Active Learning and Just-in-Time Teaching in a Material and Energy Balances Course

Science.gov (United States)

Liberatore, Matthew W.

2013-01-01

The delivery of a material and energy balances course is enhanced through a series of in-class and out-of-class exercises. An active learning classroom is achieved, even at class sizes over 150 students, using multiple instructors in a single classroom, problem solving in teams, problems based on YouTube videos, and just-in-time teaching. To avoid…

Investigation of the Relationship between Learning Process and Learning Outcomes in E-Learning Environments

Science.gov (United States)

Yurdugül, Halil; Menzi Çetin, Nihal

2015-01-01

Problem Statement: Learners can access and participate in online learning environments regardless of time and geographical barriers. This brings up the umbrella concept of learner autonomy that contains self-directed learning, self-regulated learning and the studying process. Motivation and learning strategies are also part of this umbrella…

Travel time tomography with local image regularization by sparsity constrained dictionary learning

Science.gov (United States)

Bianco, M.; Gerstoft, P.

2017-12-01

We propose a regularization approach for 2D seismic travel time tomography which models small rectangular groups of slowness pixels, within an overall or `global' slowness image, as sparse linear combinations of atoms from a dictionary. The groups of slowness pixels are referred to as patches and a dictionary corresponds to a collection of functions or `atoms' describing the slowness in each patch. These functions could for example be wavelets.The patch regularization is incorporated into the global slowness image. The global image models the broad features, while the local patch images incorporate prior information from the dictionary. Further, high resolution slowness within patches is permitted if the travel times from the global estimates support it. The proposed approach is formulated as an algorithm, which is repeated until convergence is achieved: 1) From travel times, find the global slowness image with a minimum energy constraint on the pixel variance relative to a reference. 2) Find the patch level solutions to fit the global estimate as a sparse linear combination of dictionary atoms.3) Update the reference as the weighted average of the patch level solutions.This approach relies on the redundancy of the patches in the seismic image. Redundancy means that the patches are repetitions of a finite number of patterns, which are described by the dictionary atoms. Redundancy in the earth's structure was demonstrated in previous works in seismics where dictionaries of wavelet functions regularized inversion. We further exploit redundancy of the patches by using dictionary learning algorithms, a form of unsupervised machine learning, to estimate optimal dictionaries from the data in parallel with the inversion. We demonstrate our approach on densely, but irregularly sampled synthetic seismic images.

Time series classification using k-Nearest neighbours, Multilayer Perceptron and Learning Vector Quantization algorithms

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2012-01-01

Full Text Available We are presenting results comparison of three artificial intelligence algorithms in a classification of time series derived from musical excerpts in this paper. Algorithms were chosen to represent different principles of classification – statistic approach, neural networks and competitive learning. The first algorithm is a classical k-Nearest neighbours algorithm, the second algorithm is Multilayer Perceptron (MPL, an example of artificial neural network and the third one is a Learning Vector Quantization (LVQ algorithm representing supervised counterpart to unsupervised Self Organizing Map (SOM.After our own former experiments with unlabelled data we moved forward to the data labels utilization, which generally led to a better accuracy of classification results. As we need huge data set of labelled time series (a priori knowledge of correct class which each time series instance belongs to, we used, with a good experience in former studies, musical excerpts as a source of real-world time series. We are using standard deviation of the sound signal as a descriptor of a musical excerpts volume level.We are describing principle of each algorithm as well as its implementation briefly, giving links for further research. Classification results of each algorithm are presented in a confusion matrix showing numbers of misclassifications and allowing to evaluate overall accuracy of the algorithm. Results are compared and particular misclassifications are discussed for each algorithm. Finally the best solution is chosen and further research goals are given.

Comparison of haptic guidance and error amplification robotic trainings for the learning of a timing-based motor task by healthy seniors.

Science.gov (United States)

Bouchard, Amy E; Corriveau, Hélène; Milot, Marie-Hélène

2015-01-01

With age, a decline in the temporal aspect of movement is observed such as a longer movement execution time and a decreased timing accuracy. Robotic training can represent an interesting approach to help improve movement timing among the elderly. Two types of robotic training-haptic guidance (HG; demonstrating the correct movement for a better movement planning and improved execution of movement) and error amplification (EA; exaggerating movement errors to have a more rapid and complete learning) have been positively used in young healthy subjects to boost timing accuracy. For healthy seniors, only HG training has been used so far where significant and positive timing gains have been obtained. The goal of the study was to evaluate and compare the impact of both HG and EA robotic trainings on the improvement of seniors' movement timing. Thirty-two healthy seniors (mean age 68 ± 4 years) learned to play a pinball-like game by triggering a one-degree-of-freedom hand robot at the proper time to make a flipper move and direct a falling ball toward a randomly positioned target. During HG and EA robotic trainings, the subjects' timing errors were decreased and increased, respectively, based on the subjects' timing errors in initiating a movement. Results showed that only HG training benefited learning, but the improvement did not generalize to untrained targets. Also, age had no influence on the efficacy of HG robotic training, meaning that the oldest subjects did not benefit more from HG training than the younger senior subjects. Using HG to teach the correct timing of movement seems to be a good strategy to improve motor learning for the elderly as for younger people. However, more studies are needed to assess the long-term impact of HG robotic training on improvement in movement timing.

Testing the scalar expectancy theory (SET) and the learning-to-time model (LeT) in a double bisection task.

Science.gov (United States)

Machado, Armando; Pata, Paulo

2005-02-01

Two theories of timing, scalar expectancy theory (SET) and learning-to-time (LeT), make substantially different assumptions about what animals learn in temporal tasks. In a test of these assumptions, pigeons learned two temporal discriminations. On Type 1 trials, they learned to choose a red key after a 1-sec signal and a green key after a 4-sec signal; on Type 2 trials, they learned to choose a blue key after a 4-sec signal and a yellow key after either an 8-sec signal (Group 8) or a 16-sec signal (Group 16). Then, the birds were exposed to signals 1 sec, 4 sec, and 16 sec in length and given a choice between novel key combinations (red or green vs. blue or yellow). The choice between the green key and the blue key was of particular significance because both keys were associated with the same 4-sec signal. Whereas SET predicted no effect of the test signal duration on choice, LeT predicted that preference for green would increase monotonically with the length of the signal but would do so faster for Group 8 than for Group 16. The results were consistent with LeT, but not with SET.

New learning : three ways to learn in a new balance

NARCIS (Netherlands)

Simons, P.R.J.

2000-01-01

Because people are learning all the time, we need criteria that can help us distinguish between better and worse kinds of learning. Organizations and societies as well as the psychology of learning ask for new learning outcomes, new learning processes and new forms of instruction. New learning

Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning

Directory of Open Access Journals (Sweden)

Yingfeng Cai

2016-01-01

Full Text Available Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods.

NFC LearnTracker: Seamless support for learning with mobile and sensor technology

NARCIS (Netherlands)

Tabuenca, Bernardo; Kalz, Marco; Specht, Marcus

2014-01-01

Lifelong learning activities are scattered along the day, in different locations and making use of multiple devices. Most of the times adults have to merge learning, work and everyday life making it difficult to have an account on how much time is devoted to learning activities and learning goals.

Integral reinforcement learning for continuous-time input-affine nonlinear systems with simultaneous invariant explorations.

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Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho

2015-05-01

This paper focuses on a class of reinforcement learning (RL) algorithms, named integral RL (I-RL), that solve continuous-time (CT) nonlinear optimal control problems with input-affine system dynamics. First, we extend the concepts of exploration, integral temporal difference, and invariant admissibility to the target CT nonlinear system that is governed by a control policy plus a probing signal called an exploration. Then, we show input-to-state stability (ISS) and invariant admissibility of the closed-loop systems with the policies generated by integral policy iteration (I-PI) or invariantly admissible PI (IA-PI) method. Based on these, three online I-RL algorithms named explorized I-PI and integral Q -learning I, II are proposed, all of which generate the same convergent sequences as I-PI and IA-PI under the required excitation condition on the exploration. All the proposed methods are partially or completely model free, and can simultaneously explore the state space in a stable manner during the online learning processes. ISS, invariant admissibility, and convergence properties of the proposed methods are also investigated, and related with these, we show the design principles of the exploration for safe learning. Neural-network-based implementation methods for the proposed schemes are also presented in this paper. Finally, several numerical simulations are carried out to verify the effectiveness of the proposed methods.

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment.

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Oblak, Ethan F; Lewis-Peacock, Jarrod A; Sulzer, James S

2017-07-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment.

Directory of Open Access Journals (Sweden)

Ethan F Oblak

2017-07-01

Full Text Available Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic and feedback timing (continuous or intermittent. Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results

Self-regulation strategy, feedback timing and hemodynamic properties modulate learning in a simulated fMRI neurofeedback environment

Science.gov (United States)

Sulzer, James S.

2017-01-01

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different

Relations between the development of future time perspective in three life domains, investment in learning, and academic achievement

NARCIS (Netherlands)

Peetsma, T.; van der Veen, I.

2011-01-01

Relations between the development of future time perspectives in three life domains (i.e., school and professional career, social relations, and leisure time) and changes in students’ investment in learning and academic achievement were examined in this study. Participants were 584 students in the

Learning during processing Word learning doesn’t wait for word recognition to finish