Trayectorias: a new model for online task-based learning

This paper discusses a framework for designing online tasks that capitalizes on the possibilities that the Internet and the Web offer for language learning. To present such a framework, we draw from constructivist theories (Brooks and Brooks, 1993) and their application to educational technology (Newby, Stepich, Lehman and Russell, 1996; Jonassen, Mayes and McAleese, 1993); second language learning and learning autonomy (Benson and Voller, 1997); and distance education (Race, 1989; White, 1999). On the one hand our model balances the requirements of the need for control and learning autonomy by the independent language learner; and on the other, the possibilities that online task-based learning offer for new reading processes by taking into account new literacy models (Schetzer and Warschauer, 2000), and the effect that the new media have on students’ knowledge construction and understanding of texts. We explain how this model works in the design of reading tasks within the specific distance learning context of the Open University, UK. Trayectorias is a tool that consists of an open problem-solving Web-quest and provides students with ‘scaffolding’ that guides their navigation around the Web whilst modelling learning approaches and new learning paradigms triggered by the medium. We then discuss a small-scale trial with a cohort of students (n = 23). This trial had a double purpose: (a) to evaluate to what extent the writing task fulfilled the investigators’ intentions; and (b) to obtain some information about the students’ perceptions of the task

Adapting robot behavior to user's capabilities: a dance instruction study.

The ALIZ-E1 projects goal is to design a robot companion able to maintain affective interactions with young users over a period of time. One of these interactions consists in teaching a dance to hospitalized children according to their capabilities. We propose a methodology for adapting both, the movements used in the dance based on the users cognitive and physical capabilities through a set of metrics, and the robots interaction based on the users personality traits

Physical Representation-based Predicate Optimization for a Visual Analytics Database

Querying the content of images, video, and other non-textual data sources requires expensive content extraction methods. Modern extraction techniques are based on deep convolutional neural networks (CNNs) and can classify objects within images with astounding accuracy. Unfortunately, these methods are slow: processing a single image can take about 10 milliseconds on modern GPU-based hardware. As massive video libraries become ubiquitous, running a content-based query over millions of video frames is prohibitive. One promising approach to reduce the runtime cost of queries of visual content is to use a hierarchical model, such as a cascade, where simple cases are handled by an inexpensive classifier. Prior work has sought to design cascades that optimize the computational cost of inference by, for example, using smaller CNNs. However, we observe that there are critical factors besides the inference time that dramatically impact the overall query time. Notably, by treating the physical representation of the input image as part of our query optimization---that is, by including image transforms, such as resolution scaling or color-depth reduction, within the cascade---we can optimize data handling costs and enable drastically more efficient classifier cascades. In this paper, we propose Tahoma, which generates and evaluates many potential classifier cascades that jointly optimize the CNN architecture and input data representation. Our experiments on a subset of ImageNet show that Tahoma's input transformations speed up cascades by up to 35 times. We also find up to a 98x speedup over the ResNet50 classifier with no loss in accuracy, and a 280x speedup if some accuracy is sacrificed.Comment: Camera-ready version of the paper submitted to ICDE 2019, In Proceedings of the 35th IEEE International Conference on Data Engineering (ICDE 2019

An Attempt to Probe the Radio Jet Collimation Regions in NGC 4278, NGC 4374 (M84), and NGC 6166

NRAO Very Long Baseline Array (VLBA) observations of NGC 4278, NGC 4374 (M84), NGC 6166, and M87 (NGC 4486) have been made at 43 GHz in an effort to image the jet collimation region. This is the first attempt to image the first three sources at 43 GHz using Very Long Baseline Interferometry (VLBI) techniques. These three sources were chosen because their estimated black hole mass and distance implied a Schwarzschild radius with large angular size, giving hope that the jet collimation regions could be studied. Phase referencing was utilize for the three sources because of their expected low flux densities. M87 was chosen as the calibrator for NGC 4374 because it satisfied the phase referencing requirements: nearby to the source and sufficiently strong. Having observed M87 for a long integration time, we have detected its sub-parsec jet, allowing us to confirm previous high resolution observations made by Junor, Biretta & Livio, who have indicated that a wide opening angle was seen near the base of the jet. Phase referencing successfully improved our image sensitivity, yielding detections and providing accurate positions for NGC 4278, NGC 4374 and NGC 6166. These sources are point dominated, but show suggestions of extended structure in the direction of the large-scale jets. However, higher sensitivity will be required to study their sub-parsec jet structure

Mengembangkan Pribadi Yang Tangguh Melalui Pengembangan Keterampilan Resilience

Menjalani kehidupan adalah sesuatu yang harus dijalani setiap makhluk ciptaan Allah SWT. Perkembangan zaman yang semakin modern menjadikan hidup semakin kompleks dan penuh tantangan, diperlukan pribadi ketangguhan, kepribadian tahan banting agar dalam menghadapi berbagai tantangan, kesulitan hidup baik sebagai pribadi maupun kelompok tangguh dalam istilah agama, merupakan pribadi yang senantiasa bersyukur atas segala apapun yang diberikan Allah SWT kepadanya apakah itu nikmat atau ujian. Untuk menjadi pribadi yang tangguh adalah tidak mudah, maka diperlukan latihan agar keterampilan pribadi yang tangguh dapat terasah sehingga apapun keadaannya dapat berprasangka baik kepada Allah SWT. Keterampilan resilience akan terlatih dengan interaksi individu dengan lingkungan, semakin individu berhasil mengatasi krisis yang dihadapi maka akan semakin meningkatkan potensi individu dalam rangka menghadapi tahapan perkembangan berikutnya. Hal itu pula yang akan menjadikan mental dan jiwa seseorang akan selalu hidup dan mempunyai energi positif yang terpancarkan. Selalu optimis dalam menhghadapi segala masalah kehidupan yang menerpa

Peran Pemikiran Heuristik pada Hubungan Persepsi Sosial dengan Munculnya Sikap terhadap Ide Penegakkan Khilafah Islamiyah di Indonesia

The spread of the idea of application of Khilafah Islamiyah (Islamic Caliphate) emerges zealously over the last few years. This phenomenon occurs especially among the younger generation. Through a quantitative approach, this research examines the theoretical model of the relationship between the need to reject the uncertainty, the social perception of the reality of a society and democratic practices, bias heuristic thinking and the attitude towards the idea of the application of khilafah Islamiyah in Indonesia. Data processed by regression analysis with 245 respondents. Based on the test results of the regression analysis, theoretical models did not fit with the data. Researchers propose a new theoretical model that does not involve variable need of uncertainty avoidance. The ‘bias-heuristic variable’ thinking proves to be an alternative mediator variable in the relationship between social perception of reality of a society, and democratic emergence and attitudes toward the idea of khilafah Islamiyah. For further research, suggested using SEM analysis. Researchers recommended the need to develop and construct the critical thinking among the younger generation, so they become more critical in addressing ideas tend to be radica

Localized systems coupled to small baths: from Anderson_{nderson} to Zeno_{eno}

We investigate what happens if an Anderson localized system is coupled to a small bath, with a discrete spectrum, when the coupling between system and bath is specially chosen so as to never localize the bath. We find that the effect of the bath on localization in the system is a non-monotonic function of the coupling between system and bath. At weak couplings, the bath facilitates transport by allowing the system to 'borrow' energy from the bath. But above a certain coupling the bath produces localization, because of an orthogonality catastrophe, whereby the bath 'dresses' the system and hence suppresses the hopping matrix element. We call this last regime the regime of "Zeno-localization", since the physics of this regime is akin to the quantum Zeno effect, where frequent measurements of the position of a particle impede its motion. We confirm our results by numerical exact diagonalization

Analysing the behaviour of robot teams through relational sequential pattern mining

This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

Fractional-order operators: Boundary problems, heat equations

The first half of this work gives a survey of the fractional Laplacian (and related operators), its restricted Dirichlet realization on a bounded domain, and its nonhomogeneous local boundary conditions, as treated by pseudodifferential methods. The second half takes up the associated heat equation with homogeneous Dirichlet condition. Here we recall recently shown sharp results on interior regularity and on $L_p$-estimates up to the boundary, as well as recent H\"older estimates. This is supplied with new higher regularity estimates in $L_2$-spaces using a technique of Lions and Magenes, and higher $L_p$-regularity estimates (with arbitrarily high H\"older estimates in the time-parameter) based on a general result of Amann. Moreover, it is shown that an improvement to spatial $C^\infty$-regularity at the boundary is not in general possible.Comment: 29 pages, updated version, to appear in a Springer Proceedings in Mathematics and Statistics: "New Perspectives in Mathematical Analysis - Plenary Lectures, ISAAC 2017, Vaxjo Sweden