Syväjohtaminen kokonaisvaltaisen oppimisen tukena Peikko Finland Oy:ssä

Tämän tutkimuksen tarkoituksena on ymmärtää yritystä oppivana organisaationa ja selvittää onko Syväjohtamisen valmennusmalli ja työkalu Peik-ko Finland Oy:lle organisaation ja yksilön oppimista tukevaa. Tutkimus on laadullinen tutkimus, jossa tutkimusaineiston muodostavat Peikko Finland Oy:n johdon ja esimiestehtävissä olevien henkilöiden teemahaastattelut. Tutkimuksen perusteella voidaan todeta, että Syväjohtamisen valmen-nusmalli on yrityksen ja yksilön oppimisen kannalta toimiva työkalu, joka ulkoisen valmennuksen jälkeen tulisi ylläpitää sisäisellä toimintamallilla. Oleellista on ulkoisen valmennuksen jatkamisen yhteydessä lisätä etukäteisinfon osuutta ennen valmennuksen alkamista. Peikko Finland Oy:ssä organisaation ja yksilön oma oppiminen edellyttää yritykseltä oppimista tukevien työkalujen ja yrityksen sisäisen toimintamallin toteuttamista, jonka avulla mahdollisestaan koko organisaation oppiminen ja yhteisten tavoitteiden ymmärtäminen.

Modèle informatique du coapprentissage des ganglions de la base et du cortex : l'apprentissage par renforcement et le développement de représentations

Tout au long de la vie, le cerveau développe des représentations de son environnement permettant à l’individu d’en tirer meilleur profit. Comment ces représentations se développent-elles pendant la quête de récompenses demeure un mystère. Il est raisonnable de penser que le cortex est le siège de ces représentations et que les ganglions de la base jouent un rôle important dans la maximisation des récompenses. En particulier, les neurones dopaminergiques semblent coder un signal d’erreur de prédiction de récompense. Cette thèse étudie le problème en construisant, à l’aide de l’apprentissage machine, un modèle informatique intégrant de nombreuses évidences neurologiques. Après une introduction au cadre mathématique et à quelques algorithmes de l’apprentissage machine, un survol de l’apprentissage en psychologie et en neuroscience et une revue des modèles de l’apprentissage dans les ganglions de la base, la thèse comporte trois articles. Le premier montre qu’il est possible d’apprendre à maximiser ses récompenses tout en développant de meilleures représentations des entrées. Le second article porte sur l'important problème toujours non résolu de la représentation du temps. Il démontre qu’une représentation du temps peut être acquise automatiquement dans un réseau de neurones artificiels faisant office de mémoire de travail. La représentation développée par le modèle ressemble beaucoup à l’activité de neurones corticaux dans des tâches similaires. De plus, le modèle montre que l’utilisation du signal d’erreur de récompense peut accélérer la construction de ces représentations temporelles. Finalement, il montre qu’une telle représentation acquise automatiquement dans le cortex peut fournir l’information nécessaire aux ganglions de la base pour expliquer le signal dopaminergique. Enfin, le troisième article évalue le pouvoir explicatif et prédictif du modèle sur différentes situations comme la présence ou l’absence d’un stimulus (conditionnement classique ou de trace) pendant l’attente de la récompense. En plus de faire des prédictions très intéressantes en lien avec la littérature sur les intervalles de temps, l’article révèle certaines lacunes du modèle qui devront être améliorées. Bref, cette thèse étend les modèles actuels de l’apprentissage des ganglions de la base et du système dopaminergique au développement concurrent de représentations temporelles dans le cortex et aux interactions de ces deux structures.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Aplicação de modelos gráficos probabilísticos computacionais em economia

O objetivo deste trabalho é testar a aplicação de um modelo gráfico probabilístico, denominado genericamente de Redes Bayesianas, para desenvolver modelos computacionais que possam ser utilizados para auxiliar a compreensão de problemas e/ou na previsão de variáveis de natureza econômica. Com este propósito, escolheu-se um problema amplamente abordado na literatura e comparou-se os resultados teóricos e experimentais já consolidados com os obtidos utilizando a técnica proposta. Para tanto,foi construído um modelo para a classificação da tendência do "risco país" para o Brasil a partir de uma base de dados composta por variáveis macroeconômicas e financeiras. Como medida do risco adotou-se o EMBI+ (Emerging Markets Bond Index Plus), por ser um indicador amplamente utilizado pelo mercado.

A tabela periódica: um recurso para a inclusão de alunos deficientes visuais nas aulas de química

Nowadays there are many reasons that aim to include people with special necessities, like those with visual deficiency, in the world of work, education, and in the society as a whole. However it is observed that when we talk about schooling inclusion, especially in High School, there is a huge gap between the theory and the practice. The lack of didactic resources, the inadequate installations, unprepared teachers, the families´ lack of information, are some of the factors that hinder the process of inclusion. Furthermore, the educators also have to deal with the roughness of the disciplinary contents and, refering to the study of Chemistry, with the use of signals related to this subject´s language. So, the objective of our research is to reflect about the apprehension of this language by the visually handicapped people, and try to contribute with their process of inclusion in the school life. On this perspective we work with the Periodic Table, which constitutes one of the indispensable tools necessary to the Chemistry learning. In order to acomplish it, the way followed by us happened in three passages. Initially, by means of a semistructured interview, we tried to get acquainted with the blind students opinion, who were participating in the research about the Periodic Table used by them throughout High School, as well as the dificulties felt when using it. After getting the answers, the Table was reelaborated to fill those students´necessities. Here, two new Tables were designed, one in Braille which shape is more compacted, and another made with high printed dots, built with sand and glue. On the third moment, the new designed Tables were tested by the students and, by means of a semi-structured interview, we tried to identify if this new resource would solve the problems concerned to the old Table. The students showed that the compacted Tables would facilitate the touch reading of the chemical elements simbols, making it clear and fast. We hope that, with the elaboration of this learning tools we can contribute with one of the elements to favor the effective participation of blind students in Chemistry classes, when studying the Periodic Table

Challenges of programming apprentice

The present article describes the challenges programming apprentices face and identifies the elements and processes that set them apart from experienced programmers. And also explains why a conventional programming languages teaching approach fails to map the programming mental model. The purpose of this discussion is to benefit from ideas and cognitive philosophies to be embedded in programming learning tools. Cognitive components are modeled as elements to be handled by the apprentices in tutoring systems while performing a programming task. In this process a mental level solution (the mental model of the program) and an implementation level solution (the program) are created. The mapping between these representations is a path followed by the student explicitly in this approach. © 2011 IEEE.

A visual tool for building synchronous generator capability curves

Synchronous generators are essential components of electric power systems. They are present both in hydro and thermal power plants, performing the function of converting mechanical into electrical energy. This paper presents a visual approach to manipulate parameters that affect operation limits of synchronous generators, using a specifically designed software. The operating characteristics of synchronous generators, for all possible modes of operation, are revised in order to link the concepts to the graphic objects. The approach matches the distance learning tool requirements and also enriches the learning process by developing student trust and understanding of the concepts involved in building synchronous machine capability curves. © 2012 IEEE.

Construção, caracterização global e local de redes biológicas

A Biologia Sistêmica visa a compreensão da vida através de modelos integrativos que enfatizem as interações entre os diferentes agentes biológicos. O objetivo é buscar por leis universais, não nas partes componentes dos sistemas mas sim nos padrões de interação dos elementos constituintes. As redes complexas biológicas são uma poderosa abstração matemática que permite a representação de grandes volumes de dados e a posterior formulação de hipóteses biológicas. Nesta tese apresentamos as redes biológicas integradas que incluem interações oriundas do metabolismo, interação física de proteínas e regulação. Discutimos sua construção e ferramentas para sua análise global e local. Apresentamos também resultados do uso de ferramentas de aprendizado de máquina que nos permitem compreender a relação entre propriedades topológicas e a essencialidade gênica e a previsão de genes mórbidos e alvos para drogas em humanos

Estilos de aprendizagem e interfaces online: aporte ao ensino presencial em saúde, na disciplina Interação Universidade-Serviço-Comunidade I da Faculdade de Medicina de Botucatu-UNESP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estilos de aprendizagem e interfaces online: aporte ao ensino presencial em saúde, na disciplina Interação Universidade-Serviço-Comunidade I da Faculdade de Medicina de Botucatu-UNESP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Una prospettiva storico-filosofica sull'evoluzione del curricolo di fisica nella scuola: problemi e innovazioni pedagogiche

Negli ultimi vent’anni sono state proposte al livello internazionale alcune analisi dei problemi per le scienze nella scuola e diverse strategie per l’innovazione didattica. Molte ricerche hanno fatto riferimento a una nuova nozione di literacy scientifica, quale sapere fondamentale dell’educazione, indipendente dalle scelte professionali successive alla scuola. L’ipotesi di partenza di questa ricerca sostiene che alcune di queste analisi e l’idea di una nuova literacy scientifica di tipo non-vocazionale mostrino notevoli limiti quando rapportate al contesto italiano. Le specificità di quest’ultimo sono state affrontate, innanzitutto, da un punto di vista comparativo, discutendo alcuni documenti internazionali sull’insegnamento delle scienze. Questo confronto ha messo in luce la difficoltà di ottenere un insieme di evidenze chiare e definitive sui problemi dell’educazione scientifica discussi da questi documenti, in particolare per quanto riguarda i dati sulla crisi delle vocazioni scientifiche e sull’attitudine degli studenti verso le scienze. Le raccomandazioni educative e alcuni progetti curricolari internazionali trovano degli ostacoli decisivi nella scuola superiore italiana anche a causa di specificità istituzionali, come particolari principi di selezione e l’articolazione dei vari indirizzi formativi. Il presente lavoro si è basato soprattutto su una ricostruzione storico-pedagogica del curricolo di fisica, attraverso l’analisi delle linee guida nazionali, dei programmi di studio e di alcuni rappresentativi manuali degli ultimi decenni. Questo esame del curricolo “programmato” ha messo in luce, primo, il carattere accademico della fisica liceale e la sua debole rielaborazione culturale e didattica, secondo, l’impatto di temi e problemi internazionali sui materiali didattici. Tale impatto ha prodotto dei cambiamenti sul piano delle finalità educative e degli strumenti di apprendimento incorporati nei manuali. Nonostante l’evoluzione di queste caratteristiche del curricolo, tuttavia, l’analisi delle conoscenze storico-filosofiche utilizzate dai manuali ha messo in luce la scarsa contestualizzazione culturale della fisica quale uno degli ostacoli principali per l’insegnamento di una scienza più rilevante e formativa.

Potential of information technology in dental education

The use of information technology (IT) in dentistry is far ranging. In order to produce a working document for the dental educator, this paper focuses on those methods where IT can assist in the education and competence development of dental students and dentists (e.g. e-learning, distance learning, simulations and computer-based assessment). Web pages and other information-gathering devices have become an essential part of our daily life, as they provide extensive information on all aspects of our society. This is mirrored in dental education where there are many different tools available, as listed in this report. IT offers added value to traditional teaching methods and examples are provided. In spite of the continuing debate on the learning effectiveness of e-learning applications, students request such approaches as an adjunct to the traditional delivery of learning materials. Faculty require support to enable them to effectively use the technology to the benefit of their students. This support should be provided by the institution and it is suggested that, where possible, institutions should appoint an e-learning champion with good interpersonal skills to support and encourage faculty change. From a global prospective, all students and faculty should have access to e-learning tools. This report encourages open access to e-learning material, platforms and programs. The quality of such learning materials must have well defined learning objectives and involve peer review to ensure content validity, accuracy, currency, the use of evidence-based data and the use of best practices. To ensure that the developers' intellectual rights are protected, the original content needs to be secure from unauthorized changes. Strategies and recommendations on how to improve the quality of e-learning are outlined. In the area of assessment, traditional examination schemes can be enriched by IT, whilst the Internet can provide many innovative approaches. Future trends in IT will evolve around improved uptake and access facilitated by the technology (hardware and software). The use of Web 2.0 shows considerable promise and this may have implications on a global level. For example, the one-laptop-per-child project is the best example of what Web 2.0 can do: minimal use of hardware to maximize use of the Internet structure. In essence, simple technology can overcome many of the barriers to learning. IT will always remain exciting, as it is always changing and the users, whether dental students, educators or patients are like chameleons adapting to the ever-changing landscape.

Rollout of CampusContent

CampusContent (CC) is a DFG-funded competence center for eLearning with its own portal. It links content and people who support sharing and reuse of high quality learning materials and codified pedagogical know-how, such as learning objectives, pedagogical scenarios, recommended learning activities, and learning paths. The heart of the portal is a distributed repository whose contents are linked to various other CampusContent portals. Integrated into each portal are user-friendly tools for designing reusable learning content, exercises, and templates for learning units and courses. Specialized authoring tools permit the configuration, adaption, and automatic generation of interactive Flash animations using Adobe's Flexbuilder technology. More coarse-grained content components such as complete learning units and entire courses, in which contents and materials taken from the repository are embedded, can be created with XML-based authoring tools. Open service interface allow the deep or shallow integration of the portal provider's preferred authoring and learning tools. The portal is built on top of the Enterprise Content Management System Alfresco, which comes with social networking functionality that has been adapted to accommmodate collaboration, sharing and reuse within trusted communities of practice.