The Booth: Bringing Out the Super Hero in You

Demo paper about the booth

Enhancing public speaking skills - an evaluation of the Presentation Trainer in the wild

Full paper presented at EC-TEL 2016

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Use of web-based formative assessment to support student learning in metabolism/nutrition unit

In 2002, an integrated basic science course was introduced into the Bachelor of Dental Sciences programme at the University of Queensland, Australia. Learning activities for the Metabolism and Nutrition unit within this integrated course included lectures, problem-based learning tutorials, computer-based self-directed learning exercises and practicals. To support student learning and assist students to develop the skills necessary to become lifelong learners, an extensive bank of formative assessment questions was set up using the commercially available package, WebCT®. Questions included short-answer, multiple-choice and extended matching questions. As significant staff time was involved in setting up the question database, the extent to which students used the formative assessment and their perceptions of its usefulness to their learning were evaluated to determine whether formative assessment should be extended to other units within the course. More than 90% of the class completed formative assessment tasks associated with learning activities scheduled in the first two weeks of the block, but this declined to less than 50% by the fourth and final week of the block. Patterns of usage of the formative assessment were also compared in students who scored in the top 10% for all assessment for the semester with those who scored in the lowest 10%. High-performing students accessed the Web-based formative assessment about twice as often as those who scored in the lowest band. However, marks for the formative assessment tests did not differ significantly between the two groups. In a questionnaire that was administered at the completion of the block, students rated the formative assessment highly, with 80% regarding it as being helpful for their learning. In conclusion, although substantial staff time was required to set up the question database, this appeared to be justified by the positive responses of the students.

A mobile robot platform for open learning based on serious games and remote laboratories

Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

Ontology-based metadata for e-learning content

Nowadays, the popularity of the Web encourages the development of Hypermedia Systems dedicated to e-learning. Nevertheless, most of the available Web teaching systems apply the traditional paper-based learning resources presented as HTML pages making no use of the new capabilities provided by the Web. There is a challenge to develop educative systems that adapt the educative content to the style of learning, context and background of each student. Another research issue is the capacity to interoperate on the Web reusing learning objects. This work presents an approach to address these two issues by using the technologies of the Semantic Web. The approach presented here models the knowledge of the educative content and the learner’s profile with ontologies whose vocabularies are a refinement of those defined on standards situated on the Web as reference points to provide semantics. Ontologies enable the representation of metadata concerning simple learning objects and the rules that define the way that they can feasibly be assembled to configure more complex ones. These complex learning objects could be created dynamically according to the learners’ profile by intelligent agents that use the ontologies as the source of their beliefs. Interoperability issues were addressed by using an application profile of the IEEE LOM- Learning Object Metadata standard.

Development of an electrochemical sensor for potassium ions based on KSr(2)Nb(5)O(15) modified electrode

In the work described by this paper, we studied the development of a selective potassium ion sensor constituted of a carbon paste electrode modified (CPEM) with a novel KSr(2)Nb(2)O(15). The material KSr(2)Nb(2)O(15) is an oxide with the tetragonal tungsten bronze structure (TTB) type are in forefront both in the area of research as well as in industrial applications. The sensor response to potassium ions was linear in the concentration range 1.26 x 10(-5) at 1.62 x 10(-3) mol L(-1) (E (mV) = 32.7 + 51.1 log [K(+)]). The sensor based KSr(2)Nb(2)O(15), of the TTB-type presented very good potentiometric response, with a slope of 51.1 mV/dec (at 25 degrees C) and detection limit for the potassium ions of 7.27 x 10(-5) mol.L(-1)

An electrochemical sensor for dipyrone determination based on nickel-salen film modified electrode

An amperometric dipyrone sensor based on a polymeric nickel-salen (salen = N,N'-ethylenebis(salicydeneiminato)) film coated platinum electrode was developed. The sensor was constructed by electropolymerization of nickel-salen complex at a platinum electrode in acetonitrile/tetrabuthylamonium perchlorate by cyclic voltammetry. After cycling the modified electrode in a 0.50 mol L-1 KCl solution, the estimated surface concentration was found to be equal to 1.29 x 10(-9) mol cm(-2). This is a typical behavior of an electrode surface immobilized with a redox couple that can usually be considered as a reversible single-electron reduction/oxidation of the nickel(II)/nickel(III) couple. A plot of the anodic current versus the dipyrone concentration for chronoamperometry (potential fixed = +0.50 V) at the sensor was linear in the 4.7 x 10(-6) to 1.1 x 10(-4) mol L-1 concentration range and the concentration limit was 1.2 x 10(-6) mol L-1. The proposed electrode is useful for the quality control and routine analysis of dipyrone in pharmaceutical formulations.

Sensor for diuron quantitation based on the P450 biomimetic catalyst nickel(II) 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine

A biomimetic sensor based on a carbon paste electrode modified with the nickel(II) 1,4,8,11,15,18,22,25-octabutoxy-29H,31H-phthalocyanine complex was developed as a reliable alternative technique for the sensitive and selective analysis of the herbicide diuron in environmental media. The sensor was evaluated using cyclic voltammetry and amperometric techniques. The best amperometric responses were obtained at 750 mV vs. Ag/AgCl (KClsat), using 0.1 mol L-1 phosphate buffer solution at pH 8.0. Under these conditions, the sensor showed a linear response for diuron concentrations between 9.9 × 10-6 and 1.5 × 10-4 mol L -1, a sensitivity of 22817 (±261) μA L mol-1, and detection and quantification limits of 6.14 × 10-6 and 2 × 10-5 mol L-1, respectively. The presence of the nickel complex in the carbon paste improved selectivity, stability, and sensitivity (which increased 700%), compared to unmodified paste. The applicability of the sensor was demonstrated using enriched environmental samples (river water and soil). © 2012 Elsevier B.V. All rights reserved.

An Electrochemical Sensor for Reducing Sugars Based on a Glassy Carbon Electrode Modified with Electropolymerized Molecularly Imprinted Poly-o-phenylenediamine Film

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ab-initio calculations for a realistic sensor: A study of CO sensors based on nitrogen-rich carbon nanotubes

The use of nanoscale low-dimensional systems could boost the sensitivity of gas sensors. In this work we simulate a nanoscopic sensor based on carbon nanotubes with a large number of binding sites using ab initio density functional electronic structure calculations coupled to the Non-Equilibrium Green's Function formalism. We present a recipe where the adsorption process is studied followed by conductance calculations of a single defect system and of more realistic disordered system considering different coverages of molecules as one would expect experimentally. We found that the sensitivity of the disordered system is enhanced by a factor of 5 when compared to the single defect one. Finally, our results from the atomistic electronic transport are used as input to a simple model that connects them to experimental parameters such as temperature and partial gas pressure, providing a procedure for simulating a realistic nanoscopic gas sensor. Using this methodology we show that nitrogen-rich carbon nanotubes could work at room temperature with extremely high sensitivity. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. [http://dx.doi.org/10.1063/1.4739280]

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

Comparison of the effects of inquiry-based cooperative learning and demonstrations in science education

The reported research project involved studying how teaching science using demonstrations, inquiry-based cooperative learning groups, or a combination of the two methods affected sixth grade students’ understanding of air pressure and density. Three different groups of students were each taught the two units using different teaching methods. Group one learned about the topics through both demonstrations and inquirybased cooperative learning, whereas group two only viewed demonstrations, and group three only participated in inquiry-based learning in cooperative learning groups. The study was designed to answer the following two questions: 1. Which teaching strategy works best for supporting student understanding of air pressure and density: demonstrations, inquirybased labs in cooperative learning groups, or a combination of the two? 2. And what effect does the time spent engaging in a particular learning experience (demonstrations or labs) have on student learning? Overall, the data did not provide sufficient evidence that one method of learning was more effective than the others. The results also suggested that spending more time on a unit does not necessarily equate to a better understanding of the concepts by the students. Implications for science instruction are discussed.

A 0.0016 mm(2) 0.64 nJ leakage-based CMOS temperature sensor

This paper presents a CMOS temperature sensor based on the thermal dependencies of the leakage currents targeting the 65 nm node. To compensate for the effect of process fluctuations, the proposed sensor realizes the ratio of two measures of the time it takes a capacitor to discharge through a transistor in the subthreshold regime. Furthermore, a novel charging mechanism for the capacitor is proposed to further increase the robustness against fabrication variability. The sensor, including digitization and interfacing, occupies 0.0016 mm2 and has an energy consumption of 47.7–633 pJ per sample. The resolution of the sensor is 0.28 °C, and the 3σ inaccuracy over the range 40–110 °C is 1.17 °C.

Graph-based Semi-Supervised Learning in Acoustic Modeling for Automatic Speech Recognition

Thesis (Ph.D.)--University of Washington, 2016-06