Evaluation of an online, case-based interactive approach to teaching pathophysiology

Rapport de synthèse : L'article qui fait l'objet de ma thèse évalue une nouvelle approche pédagogique pour l'apprentissage de certains chapitres de physiopathologie. Le dispositif pédagogique se base sur l'alternance d'apprentissage ex-cathedra et de l'utilisation d'un site web comprenant des vignettes cliniques. Lors de la consultation de ces-dernières, l'étudiant est invité à demander des examens de laboratoire dont il pourrait justifier la pertinence selon le cas clinique étudié. La nouveauté du procédé réside dans le fait que, préalablement à son cours ex-cathedra, l'enseignant peut consulter les statistiques de demandes de laboratoire et ainsi orienter son cours selon les éléments mal compris par les étudiants. A la suite du cours ex-cathedra, les étudiants peuvent consulter sur internet la vignette clinique complète avec des explications. A l'issue de tout le cours, une évaluation auprès des étudiants a été conduite. Le procédé a été mis en place durant deux années consécutives et l'article en discute notamment les résultats. Nous avons pu conclure que cette méthode innovatrice d'enseignement amène les étudiants à mieux se préparer pour les cours ex-cathedra tout en permettant à l'enseignant d'identifier plus précisément quelles thématiques étaient difficiles pour les étudiants et donc d'ajuster au mieux son cours. Mon travail de thèse a consisté à créer ce dispositif d'apprentissage, à créer l'application web des vignettes cliniques et à l'implanter durant deux années consécutives. J'ai ensuite analysé les données des évaluations et écrit l'article que j'ai présenté à la revue 'Medical Teacher'. Après quelques corrections et précisions demandées par le comité de lecture, l'article a été accepté et publié. Ce travail a débouché sur une seconde version de l'application web qui est actuellement utilisée lors du module 3.1 de 3è année à l'Ecole de Médecine à Lausanne. Summary : Since the early days of sexual selection, our understanding of the selective forces acting on males and females during reproduction has increased remarkably. However, despite a long tradition of experimental and theoretical work in this field and relentless effort, numerous questions remain unanswered and many results are conflicting. Moreover, the interface between sexual selection and conservation biology has to date received little attention, despite existing evidence for its importance. In the present thesis, I first used an empirical approach to test various sexual selection hypotheses in a population of whitefish of central Switzerland. This precise population is characterized by a high prevalence of gonadal alterations in males. In particular, I challenged the hypothesis that whitefish males displaying peculiar gonadal features are of lower genetic quality than other seemingly normal males. Additionally, I also worked on identifying important determinant of sperm behavior. During a second theoretical part of my work, which is part of a larger project on the evolution of female mate preferences in harvested fish populations, I developed an individual-based simulation model to estimate how different mate discrimination costs affect the demographical behavior of fish populations and the evolutionary trajectories of female mate preferences. This latter work provided me with some insight on a recently published article addressing the importance of sexual selection for harvesting-induced evolution. I built upon this insight in a short perspective paper. In parallel, I let some methodological questions drive my thoughts, and wrote an essay about possible synergies between the biological, the philosophical and the statistical approach to biological questions.

Reflexiones sobre los cyborgs y los robots: evolucion humana y aumentacion

The human being has changed in time due to both, biological and cultural evolution. In a first step, biological evolution was the cornerstone of the changes in our species. However, cultural evolution was also a key element producing adaptations that allowed the evolution of modern human being. These adaptations include aspects as different as clothing, tools, reading and writing, calculation and some forms of rudimentary prosthesis. Technoscience has enhanced these adaptations that conduce to the concept of broad-sense cyborg. Present human society includes a huge proportion of these latter individuals. In this article we discuss this reality and the future of our society based on the interconnections between humans, cyborgs and robots.

The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

A Robust Multiple Feature Approach To Endpoint Detection In Car Environment Based On Advanced Classifiers

In this paper we propose an endpoint detection system based on the use of several features extracted from each speech frame, followed by a robust classifier (i.e Adaboost and Bagging of decision trees, and a multilayer perceptron) and a finite state automata (FSA). We present results for four different classifiers. The FSA module consisted of a 4-state decision logic that filtered false alarms and false positives. We compare the use of four different classifiers in this task. The look ahead of the method that we propose was of 7 frames, which are the number of frames that maximized the accuracy of the system. The system was tested with real signals recorded inside a car, with signal to noise ratio that ranged from 6 dB to 30dB. Finally we present experimental results demonstrating that the system yields robust endpoint detection.

A Secure Mobile-based Authentication System

Financial information is extremely sensitive. Hence, electronic banking must provide a robust system to authenticate its customers and let them access their data remotely. On the other hand, such system must be usable, affordable, and portable.We propose a challengeresponse based one-time password (OTP) scheme that uses symmetriccryptography in combination with a hardware security module. The proposed protocol safeguards passwords from keyloggers and phishing attacks.Besides, this solution provides convenient mobility for users who want to bank online anytime and anywhere, not just from their owntrusted computers.

An embedded real-time red peach detection system based on an OV7670 camera, ARM Cortex-M4 processor and 3D Look-Up Tables

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

Optimizing the Testing Process in Module Testing – Functional Testing Interface

Today's business environment has become increasingly unexpected and fast changing because of the global competition. This new environment requires the companies to organize their control differently, e.g. by logistic process thinking. Logistic process thinking in software engineering applies the principles of production process to immaterial products. Processes must be optimized, so that every phase adds value to the customer, and the lead times can be cut shorter to meet the new customer requirements. The purpose of this thesis is to examine and optimize the testing processes of software engineering concentrating on module testing, functional testing and their interface. The concept of logistic process thinking is introduced through production process, value added model and process management. Also theory of testing based on literature is presented, concentrating on module testing and functional testing. The testing processes of the Case Company are presented together with the project models in which they are implemented. The real life practices in module testing and functional testing and their interface are examined through interviews. These practices are analyzed against the processes and the testing theory, through which ideas for optimizing the testing process are introduced. The project world of the Case Company is also introduced together with two example testing projects in different life cycle phases. The examples give a view of how much effort of the project is put in different types of testing.

Robots and robotic systems for the electronics and telecommunication industry

Tämä diplomityö tutkii elektroniikka- ja telekommunikaatioteollisuutta sekä siihen läheisesti liittyviä robotteja ja robottijärjestelmiä. Tavoitteena on määrittää E&T-teollisuuden prosesseihin soveltuvien robottien testausmenetelmä. Tavoitteena on myös selvittää kahden ABB:n robotin soveltuvuutta E&T-teollisuuden tarpeisiin. Muutamia systemaattisia valmistusjärjestelmien suunnitteluun soveltuvia menetelmiä ja apuvälineitä on myös käsitelty. Alussa työ keskittyy elektroniikka- ja telekommunikaatioteollisuuden nykytilan tutkimiseen sekä siellä vallitsevien ja ennustettujen trendien kartoitukseen. Kohdat “Collaborative manufacturing” ja E&T-teollisuuden valmistusjärjestelmille asettamat vaatimukset käydään yksityiskohtaisesti läpi. Tutkimuksen pääkohteina ovat robotit, erityisesti ABB:n IRB 140 ja IRB 340 sekä robottien testausmenetelmän määrittäminen. Työssä käydään läpi IRB 340:llä suoritetut testit, jotka tehtiin sekä konenäköjärjestelmää apuna käyttäen että ilman. Myös TTKK:lla suoritetut robottitestit on käyty läpi. Robottien testituloksia on analysoitu ja vertailtu muihin robotteihin. Testausmenetelmät perustuvat ISO 9283 standardiin. Viimeinen osa työstä esittelee robottijärjestelmien systemaattiseen suunnitteluun soveltuvia menetelmiä ja apuvälineitä. Esillä ovat mm. Modular function deployment (MFD) ja The system design method (SDM).

Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

PeerHood as UMSIC middleware module

The UMSIC project will produce an application for social inclusion of children. This application will run on Nokia N810 internet tablet. PeerHood is an implementation of Peer-to-Peer neighborhood and communication concept, it is going to be used as a part of middleware in the project. PeerHood is responsible for providing neighboring information and connections to nearby devices. This thesis will present the requirements that the project sets to PeerHood including the general state of the art middleware requirements and the requirements set by the target device. These requirements will not be analyzed further. One main focus of this thesis is to analyze PeerHood from the UMSIC project point of view. In this thesis the results of PeerHood analysis are presented, including memory consumption testing, performance testing and testing of networking components of PeerHood. As a result of these tests modifications for PeerHood are introduced. The modifications are related to PeerHood usage in real mobile environment. Based on these requirements a framework was implemented that, when used properly, will enhance the context awareness of PeerHood, especially in mobile devices. The techniques used in framework are presented and instructions about how to use the framework are given. The approaches used in the implemented framework are analysed in this thesis. As an outcome of this thesis the context awareness of PeerHood is improved. As an additional outcome the guidelines for future development of PeerHood are introduced that are based on the results of the analysis of both PeerHood and the implemented framework.

Power cycling lifetime estimation of IGBT power modules based on chip temperature modeling

In this doctoral thesis, methods to estimate the expected power cycling life of power semiconductor modules based on chip temperature modeling are developed. Frequency converters operate under dynamic loads in most electric drives. The varying loads cause thermal expansion and contraction, which stresses the internal boundaries between the material layers in the power module. Eventually, the stress wears out the semiconductor modules. The wear-out cannot be detected by traditional temperature or current measurements inside the frequency converter. Therefore, it is important to develop a method to predict the end of the converter lifetime. The thesis concentrates on power-cycling-related failures of insulated gate bipolar transistors. Two types of power modules are discussed: a direct bonded copper (DBC) sandwich structure with and without a baseplate. Most common failure mechanisms are reviewed, and methods to improve the power cycling lifetime of the power modules are presented. Power cycling curves are determined for a module with a lead-free solder by accelerated power cycling tests. A lifetime model is selected and the parameters are updated based on the power cycling test results. According to the measurements, the factor of improvement in the power cycling lifetime of modern IGBT power modules is greater than 10 during the last decade. Also, it is noticed that a 10 C increase in the chip temperature cycle amplitude decreases the lifetime by 40%. A thermal model for the chip temperature estimation is developed. The model is based on power loss estimation of the chip from the output current of the frequency converter. The model is verified with a purpose-built test equipment, which allows simultaneous measurement and simulation of the chip temperature with an arbitrary load waveform. The measurement system is shown to be convenient for studying the thermal behavior of the chip. It is found that the thermal model has a 5 C accuracy in the temperature estimation. The temperature cycles that the power semiconductor chip has experienced are counted by the rainflow algorithm. The counted cycles are compared with the experimentally verified power cycling curves to estimate the life consumption based on the mission profile of the drive. The methods are validated by the lifetime estimation of a power module in a direct-driven wind turbine. The estimated lifetime of the IGBT power module in a direct-driven wind turbine is 15 000 years, if the turbine is located in south-eastern Finland.

Experimental validation of a 3-D vision-based measurement system applied to robot calibration

One of the problems that slows the development of off-line programming is the low static and dynamic positioning accuracy of robots. Robot calibration improves the positioning accuracy and can also be used as a diagnostic tool in robot production and maintenance. A large number of robot measurement systems are now available commercially. Yet, there is a dearth of systems that are portable, accurate and low cost. In this work a measurement system that can fill this gap in local calibration is presented. The measurement system consists of a single CCD camera mounted on the robot tool flange with a wide angle lens, and uses space resection models to measure the end-effector pose relative to a world coordinate system, considering radial distortions. Scale factors and image center are obtained with innovative techniques, making use of a multiview approach. The target plate consists of a grid of white dots impressed on a black photographic paper, and mounted on the sides of a 90-degree angle plate. Results show that the achieved average accuracy varies from 0.2mm to 0.4mm, at distances from the target from 600mm to 1000mm respectively, with different camera orientations.

AOD 2.0: A category based submission add-on for DSpace 4.0

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014