Machine translation and the disruption of foreign language learning activities

This study examines the question of how language teachers in a highly technology-friendly university environment view machine translation and the implications that this has for the personal learning environments of students. It brings an activity-theory perspective to the question, examining the ways that the introduction of new tools can disrupt the relationship between different elements in an activity system. This perspective opens up for an investigation of the ways that new tools have the potential to fundamentally alter traditional learning activities. In questionnaires and group discussions, respondents showed general agreement that although use of machine translation by students could be considered cheating, students are bound to use it anyway, and suggested that teachers focus on the kinds of skills students would need when using machine translation and design assignments and exams to practice and assess these skills. The results of the empirical study are used to reflect upon questions of what the roles of teachers and students are in a context where many of the skills that a person needs to be able to interact in a foreign language increasingly can be outsourced to laptops and smartphones.

From a traditional academic library to a modern learning environment : Dalarna University Library - expectations and results

This report describes the ideas and vision behind Dalarna University's award-winning library in Falun. A description of the planning and construction processes and an evaluation of the final outcome are presented together with experiences and observations drawn from the project.

Automatic Classification of Three-Phase Flow Patterns of Heavy Oil in a Horizontal Pipe Using Support Vector Machines

The pipe flow of a viscous-oil-gas-water mixture such as that involved in heavy oil production is a rather complex thereto-fluid dynamical problem. Considering the complexity of three-phase flow, it is of fundamental importance the introduction of a flow pattern classification tool to obtain useful information about the flow structure. Flow patterns are important because they indicate the degree of mixing during flow and the spatial distribution of phases. In particular, the pressure drop and temperature evolution along the pipe is highly dependent on the spatial configuration of the phases. In this work we investigate the three-phase water-assisted flow patterns, i.e. those configurations where water is injected in order to reduce friction caused by the viscous oil. Phase flow rates and pressure drop data from previous laboratory experiments in a horizontal pipe are used for flow pattern identification by means of the 'support vector machine' technique (SVM).

Precipitates segmentation from scanning electron microscope images through machine learning techniques

The presence of precipitates in metallic materials affects its durability, resistance and mechanical properties. Hence, its automatic identification by image processing and machine learning techniques may lead to reliable and efficient assessments on the materials. In this paper, we introduce four widely used supervised pattern recognition techniques to accomplish metallic precipitates segmentation in scanning electron microscope images from dissimilar welding on a Hastelloy C-276 alloy: Support Vector Machines, Optimum-Path Forest, Self Organizing Maps and a Bayesian classifier. Experimental results demonstrated that all classifiers achieved similar recognition rates with good results validated by an expert in metallographic image analysis. © 2011 Springer-Verlag Berlin Heidelberg.

Desempenho oral em português para falantes de outras línguas: da avaliação à aprendizagem de línguas estrangeiras em contexto online

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Flow Boiling Characteristics for R1234ze(E) in 1.0 and 2.2 mm Circular Channels

Experimental flow boiling heat transfer results are presented for horizontal 1.0 and 2.2 mm I. D. (internal diameter) stainless steel tubes for tests with R1234ze(E), a new refrigerant developed as a substitute for R134a with a much lower global warming potential (GWP). The experiments were performed for these two tube diameters in order to investigate a possible transition between macro and microscale flow boiling behavior. The experimental campaign includes mass velocities ranging from 50 to 1500 kg/m(2) s, heat fluxes from 10 to 300 kW/m(2), exit saturation temperatures of 25, 31 and 35 degrees C, vapor qualities from 0.05 to 0.99 and heated lengths of 180 mm and 361 mm. Flow pattern characterization was performed using high speed videos. Heat transfer coefficient, critical heat flux and flow pattern data were obtained. R1234ze(E) demonstrated similar thermal performance to R134a data when running at similar conditions. [DOI: 10.1115/1.4004933]

Water-assisted Flow of Heavy Oil in a Vertical Pipe: Pilot-scale Experiments

The use of the core-annular flow pattern, where a thin fluid surrounds a very viscous one, has been suggested as an attractive artificial-lift method for heavy oils in the current Brazilian ultra-deepwater production scenario. This paper reports the pressure drop measurements and the core-annular flow observed in a 2 7/8-inch and 300 meter deep pilot-scale well conveying a mixture of heavy crude oil (2000 mPa.s and 950 kg/m3 at 35 C) and water at several combinations of the individual flow rates. The two-phase pressure drop data are compared with those of single-phase oil flow to assess the gains due to water injection. Another issue is the handling of the core-annular flow once it has been established. High-frequency pressure-gradient signals were collected and a treatment based on the Gabor transform together with neural networks is proposed as a promising solution for monitoring and control. The preliminary results are encouraging. The pilot-scale tests, including long-term experiments, were conducted in order to investigate the applicability of using water to transport heavy oils in actual wells. It represents an important step towards the full scale application of the proposed artificial-lift technology. The registered improvements in terms of oil production rate and pressure drop reductions are remarkable.

Two-phase flow patterns and pressure drop inside horizontal tubes containing twisted-tape inserts

This paper presents an experimental study on two-phase flow patterns and pressure drop of R134a inside a 15.9 mm ID tube containing twisted-tape inserts. Experimental results were obtained in a horizontal test section for twisted-tape ratios of 3, 4, 9 and 14, mass velocities ranging from 75 to 250 kg/m(2) s and saturation temperatures of 5 and 15 degrees C. An unprecedented discussion on two-phase flow patterns inside tubes containing twisted-tape inserts is presented and the flow pattern effects on the frictional pressure drop are carefully discussed. Additionally, a new method to predict the frictional pressure drop during two-phase flow inside tubes containing twisted-tape inserts is proposed. (C) 2012 Elsevier Ltd. All rights reserved.

Amazon Rainforest Exchange of Carbon and Subcanopy Air Flow: Manaus LBA Site-A Complex Terrain Condition

On the moderately complex terrain covered by dense tropical Amazon Rainforest (Reserva Biologica do Cuieiras-ZF2-02 degrees 36'17.1 '' S, 60 degrees 12'24.4 '' W), subcanopy horizontal and vertical gradients of the air temperature, CO2 concentration and wind field were measured for the dry and wet periods in 2006. We tested the hypothesis that horizontal drainage flow over this study area is significant and can affect the interpretation of the high carbon uptake rates reported by previous works at this site. A similar experimental design as the one by Tota et al. (2008) was used with a network of wind, air temperature, and CO2 sensors above and below the forest canopy. A persistent and systematic subcanopy nighttime upslope (positive buoyancy) and daytime downslope (negative buoyancy) flow pattern on a moderately inclined slope (12%) was observed. The microcirculations observed above the canopy (38 m) over the sloping area during nighttime presents a downward motion indicating vertical convergence and correspondent horizontal divergence toward the valley area. During the daytime an inverse pattern was observed. The microcirculations above the canopy were driven mainly by buoyancy balancing the pressure gradient forces. In the subcanopy space the microcirculations were also driven by the same physical mechanisms but probably with the stress forcing contribution. The results also indicated that the horizontal and vertical scalar gradients (e. g., CO2) were modulated by these micro-circulations above and below the canopy, suggesting that estimates of advection using previous experimental approaches are not appropriate due to the tridimensional nature of the vertical and horizontal transport locally. This work also indicates that carbon budget from tower-based measurement is not enough to close the system, and one needs to include horizontal and vertical advection transport of CO2 into those estimates.

Geometrical and kinematic properties of interfacial waves in stratified oil-water flow in inclined pipe

The stratified oil-water flow pattern is common in the petroleum industry, especially in offshore directional wells and pipelines. Previous studies have shown that the phenomenon of flow pattern transition in stratified flow can be related to the interfacial wave structure (problem of hydrodynamic instability). The study of the wavy stratified flow pattern requires the characterization of the interfacial wave properties, i.e., average shape, celerity and geometric properties (amplitude and wavelength) as a function of holdup, inclination angle and phases' relative velocity. However, the data available in the literature on wavy stratified flow is scanty, especially in inclined pipes and when oil is viscous. This paper presents new geometric and kinematic interfacial wave properties as a function of a proposed two-phase Froude number in the wavy-stratified liquid-liquid flow. The experimental work was conducted in a glass test line of 12 m and 0.026 m id., oil (density and viscosity of 828 kg/m(3) and 0.3 Pa s at 20 degrees C, respectively) and water as the working fluids at several inclinations from horizontal (-20 degrees, -10 degrees, 0 degrees, 10 degrees, 20 degrees). The results suggest a physical relation between wave shape and the hydrodynamic stability of the stratified liquid-liquid flow pattern. (C) 2011 Elsevier Inc. All rights reserved.

Formazione, apprendimento e nuove prospettive e-learning. Lo sviluppo delle nuove tecnologie didattiche e la creazione di sistemi di apprendimento lungo l’intero arco della vita

The thesis of this paper is based on the assumption that the socio-economic system in which we are living is characterised by three great trends: growing attention to the promotion of human capital; extremely rapid technological progress, based above all on the information and communication technologies (ICT); the establishment of new production and organizational set-ups. These transformation processes pose a concrete challenge to the training sector, which is called to satisfy the demand for new skills that need to be developed and disseminated. Hence the growing interest that the various training sub-systems devote to the issues of lifelong learning and distance learning. In such a context, the so-called e-learning acquires a central role. The first chapter proposes a reference theoretical framework for the transformations that are shaping post-industrial society. It analyzes some key issues such as: how work is changing, the evolution of organizational set-ups and the introduction of learning organization, the advent of the knowledge society and of knowledge companies, the innovation of training processes, and the key role of ICT in the new training and learning systems. The second chapter focuses on the topic of e-learning as an effective training model in response to the need for constant learning that is emerging in the knowledge society. This chapter starts with a reflection on the importance of lifelong learning and introduces the key arguments of this thesis, i.e. distance learning (DL) and the didactic methodology called e-learning. It goes on with an analysis of the various theoretic and technical aspects of e-learning. In particular, it delves into the theme of e-learning as an integrated and constant training environment, characterized by customized programmes and collaborative learning, didactic assistance and constant monitoring of the results. Thus, all the aspects of e-learning are taken into exam: the actors and the new professionals, the virtual communities as learning subjects, the organization of contents in learning objects, the conformity to international standards, the integrated platforms and so on. The third chapter, which concludes the theoretic-interpretative part, starts with a short presentation of the state-of-the-art e-learning international market that aims to understand its peculiarities and its current trends. Finally, we focus on some important regulation aspects related to the strong impulse given by the European Commission first, and by the Italian governments secondly, to the development and diffusion of e-learning. The second part of the thesis (chapters 4, 5 and 6) focus on field research, which aims to define the Italian scenario for e-learning. In particular, we have examined some key topics such as: the challenges of training and the instruments to face such challenges; the new didactic methods and technologies for lifelong learning; the level of diffusion of e-learning in Italy; the relation between classroom training and online training; the main factors of success as well as the most critical aspects of the introduction of e-learning in the various learning environments. As far as the methodological aspects are concerned, we have favoured a qualitative and quantitative analysis. A background analysis has been done to collect the statistical data available on this topic, as well as the research previously carried out in this area. The main source of data is constituted by the results of the Observatory on e-learning of Aitech-Assinform, which covers the 2000s and four areas of implementation (firms, public administration, universities, school): the thesis has reviewed the results of the last three available surveys, offering a comparative interpretation of them. We have then carried out an in-depth empirical examination of two case studies, which have been selected by virtue of the excellence they have achieved and can therefore be considered advanced and emblematic experiences (a large firm and a Graduate School).

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

The simultaneous role of an alveolus as flow mixer and flow feeder for the deposition of inhaled submicron particles

In an effort to understand the fate of inhaled submicron particles in the small sacs, or alveoli, comprising the gas-exchange region of the lung, we calculated the flow in three-dimensional (3D) rhythmically expanding models of alveolated ducts. Since convection toward the alveolar walls is a precursor to particle deposition, it was the goal of this paper to investigate the streamline maps' dependence upon alveoli location along the acinar tree. On the alveolar midplane, the recirculating flow pattern exhibited closed streamlines with a stagnation saddle point. Off the midplane we found no closed streamlines but nested, funnel-like, spiral, structures (reminiscent of Russian nesting dolls) that were directed towards the expanding walls in inspiration, and away from the contracting walls in expiration. These nested, funnel-like, structures were surrounded by air that flowed into the cavity from the central channel over inspiration and flowed from the cavity to the central channel over expiration. We also found that fluid particle tracks exhibited similar nested funnel-like spiral structures. We conclude that these unique alveolar flow structures may be of importance in enhancing deposition. In addition, due to inertia, the nested, funnel-like, structures change shape and position slightly during a breathing cycle, resulting in flow mixing. Also, each inspiration feeds a fresh supply of particle-laden air from the central channel to the region surrounding the mixing region. Thus, this combination of flow mixer and flow feeder makes each individual alveolus an effective mixing unit, which is likely to play an important role in determining the overall efficiency of convective mixing in the acinus.

The role of the sinuses of Valsalva in aortic root flow dynamics and aortic root surgery: evaluation by magnetic resonance imaging

BACKGROUND AND AIM OF THE STUDY: Combined replacement of the aortic valve and ascending aorta using a composite graft represents the standard treatment for dilated aortic root with concomitant structural damage of the aortic valve, especially when the aortic valve cannot be preserved. Unfortunately, hemodynamic changes associated with prosthetic replacement of the aortic root have not been fully elucidated. The study aim was to compare hemodynamics within the replaced aortic root using either a prosthetic vascular graft with bulges mimicking the sinuses of Valsalva and including a stented pericardial valve, or a straight xenopericardial conduit and a stentless porcine valve. METHODS: Between July 2004 and March 2006, a total of 35 patients (mean age 65.2 years: range: 32-80 years) was enrolled into the present study. Aortic root replacement was performed in nine patients with a Valsalva graft (Gelweave Valsalva; Vascutek, Renfrewshire, UK) including a stented pericardial valve, and in 19 patients with a xenopericardial conduit containing a stentless porcine valve. All patients underwent postoperative magnetic resonance imaging (MRI). A control group of seven patients allowed for comparison with native aortic root hemodynamics. RESULTS: Maximum flow-velocity above the aortic valve as one marker of compliance of the aortic root was slightly higher in patients with a Valsalva graft compared to native aortic roots (1.9 m/s versus 1.3 m/s, p = 0.001), but was significantly lower than in patients with the xenopericardial graft without neo-sinuses (1.3 m/s versus 2.4 m/s, p < 0.001). CONCLUSION: The pre-shaped bulges in the prosthetic Valsalva graft effectively mimic the native sinuses of Valsalva, improve compliance of the aortic root, and result in a more physiologic flow pattern, as demonstrated by postoperative MRI.

Mobile Games for Learning

Today, pupils at the age of 15 have spent their entire life surrounded by and interacting with diverse forms of computers. It is a routine part of their day-to-day life and by now computer-literacy is common at very early age. Over the past five years, technology for teens has become predominantly mobile and ubiquitous within every aspect of their lives. To them, being online is an implicitness. In Germany, 88% of youth aged between 12-19 years own a smartphone and about 20% use the Internet via tablets. Meanwhile, more and more young learners bring their devices into the classroom and pupils increasingly demand for innovative and motivating learning scenarios that strongly respond to their habits of using media. With this development, a shift of paradigm is slowly under way with regard to the use of mobile technology in education. By now, a large body of literature exists, that reports concepts, use-cases and practical studies for effectively using technology in education. Within this field, a steadily growing body of research has developed that especially examines the use of digital games as instructional strategy. The core concern of this thesis is the design of mobile games for learning. The conditions and requirements that are vital in order to make mobile games suitable and effective for learning environments are investigated. The base for exploration is the pattern approach as an established form of templates that provide solutions for recurrent problems. Building on this acknowledged form of exchanging and re-using knowledge, patterns for game design are used to classify the many gameplay rules and mechanisms in existence. This research draws upon pattern descriptions to analyze learning game concepts and to abstract possible relationships between gameplay patterns and learning outcomes. The linkages that surface are the starting bases for a series of game design concepts and their implementations are subsequently evaluated with regard to learning outcomes. The findings and resulting knowledge from this research is made accessible by way of implications and recommendations for future design decisions.