On the Condition Monitoring of Induction machines

The research of condition monitoring of electric motors has been wide for several decades. The research and development at universities and in industry has provided means for the predictive condition monitoring. Many different devices and systems are developed and are widely used in industry, transportation and in civil engineering. In addition, many methods are developed and reported in scientific arenas in order to improve existing methods for the automatic analysis of faults. The methods, however, are not widely used as a part of condition monitoring systems. The main reasons are, firstly, that many methods are presented in scientific papers but their performance in different conditions is not evaluated, secondly, the methods include parameters that are so case specific that the implementation of a systemusing such methods would be far from straightforward. In this thesis, some of these methods are evaluated theoretically and tested with simulations and with a drive in a laboratory. A new automatic analysis method for the bearing fault detection is introduced. In the first part of this work the generation of the bearing fault originating signal is explained and its influence into the stator current is concerned with qualitative and quantitative estimation. The verification of the feasibility of the stator current measurement as a bearing fault indicatoris experimentally tested with the running 15 kW induction motor. The second part of this work concentrates on the bearing fault analysis using the vibration measurement signal. The performance of the micromachined silicon accelerometer chip in conjunction with the envelope spectrum analysis of the cyclic bearing faultis experimentally tested. Furthermore, different methods for the creation of feature extractors for the bearing fault classification are researched and an automatic fault classifier using multivariate statistical discrimination and fuzzy logic is introduced. It is often important that the on-line condition monitoring system is integrated with the industrial communications infrastructure. Two types of a sensor solutions are tested in the thesis: the first one is a sensor withcalculation capacity for example for the production of the envelope spectra; the other one can collect the measurement data in memory and another device can read the data via field bus. The data communications requirements highly depend onthe type of the sensor solution selected. If the data is already analysed in the sensor the data communications are needed only for the results but in the other case, all measurement data need to be transferred. The complexity of the classification method can be great if the data is analysed at the management level computer, but if the analysis is made in sensor itself, the analyses must be simple due to the restricted calculation and memory capacity.

Nonlinear prediction based on score function

The linear prediction coding of speech is based in the assumption that the generation model is autoregresive. In this paper we propose a structure to cope with the nonlinear effects presents in the generation of the speech signal. This structure will consist of two stages, the first one will be a classical linear prediction filter, and the second one will model the residual signal by means of two nonlinearities between a linear filter. The coefficients of this filter are computed by means of a gradient search on the score function. This is done in order to deal with the fact that the probability distribution of the residual signal still is not gaussian. This fact is taken into account when the coefficients are computed by a ML estimate. The algorithm based on the minimization of a high-order statistics criterion, uses on-line estimation of the residue statistics and is based on blind deconvolution of Wiener systems [1]. Improvements in the experimental results with speech signals emphasize on the interest of this approach.

Method development for the simultaneous determination of methylmercury and inorganic mercury in seafood

This paper reports the method development for the simultaneous determination of methylmercury MeHgþ) and inorganic mercury (iHg) species in seafood samples. The study focused on the extraction and quantification of MeHgþ (the most toxic species) by liquid chromatography coupled to on-line UV irradiation and cold vapour atomic fluorescence spectroscopy (LC-UV-CV-AFS), using HCl 4 mol/L as the extractant agent. Accuracy of the method has been verified by analysing three certified reference materials and different spiked samples. The values found for total Hg and MeHgþ for the CRMs did not differ significantly from certified values at a 95% confidence level, and recoveries between 85% and 97% for MeHgþ, based on spikes, were achieved. The detection limits (LODs) obtained were 0.001 mg Hg/kg for total mercury, 0.0003 mg Hg/kg for MeHgþ and 0.0004 mg Hg/kg for iHg. The quantification limits (LOQs) established were 0.003 mg Hg/kg for total mercury, 0.0010 mg Hg/kg for MeHgþ and 0.0012 mg Hg/kg for iHg. Precision for each mercury species was established, being 12% in terms of RSD in all cases. Finally, the developed method was applied to 24 seafood samples from different origins and total mercury contents. The concentrations for Total Hg, MeHg and iHg ranged from 0.07 to 2.33, 0.003-2.23 and 0.006-0.085 mg Hg/kg, respectively. The established analytical method allows to obtain results for mercury speciation in less than 1 one hour including both, sample pretreatment and measuring step.

Wavelets in real-time paper web analysis

Online paper web analysis relies on traversing scanners that criss-cross on top of a rapidly moving paper web. The sensors embedded in the scanners measure many important quality variables of paper, such as basis weight, caliper and porosity. Most of these quantities are varying a lot and the measurements are noisy at many different scales. The zigzagging nature of scanning makes it difficult to separate machine direction (MD) and cross direction (CD) variability from one another. For improving the 2D resolution of the quality variables above, the paper quality control team at the Department of Mathematics and Physics at LUT has implemented efficient Kalman filtering based methods that currently use 2D Fourier series. Fourier series are global and therefore resolve local spatial detail on the paper web rather poorly. The target of the current thesis is to study alternative wavelet based representations as candidates to replace the Fourier basis for a higher resolution spatial reconstruction of these quality variables. The accuracy of wavelet compressed 2D web fields will be compared with corresponding truncated Fourier series based fields.

La formulación magistral: adquisición de compètencias mediante ABP y estrategias no presenciales

[cast] La formulación magistral, una de las actividades profesionales más representativas del farmacéutico, consiste en la elaboración, de acuerdo con una prescripción médica, de un medicamento personalizado, adaptado a un paciente concreto, en un compromiso profesional de solucionar un problema de salud específico. La amplia oferta de medicamentos industriales ha reducido considerablemente esta actividad, que a pesar de todo, debe considerarse una herramienta de futuro en sintonía con la tendencia personalizadora actual de la medicina y las necesidades del paciente. Los conocimientos y competencias requeridas para dicha actividad profesional se introducen actualmente en la carrera de Farmacia mediante una asignatura optativa. En el presente trabajo se presenta el planteamiento metodológico diseñado por el Grupo de Innovación Docente de Tecnología Farmacéutica (GIDTF) y el grupo e-Galenica, ambos de la Universidad de Barcelona, para esta asignatura. Dicha metodología esta basada en el Aprendizaje Basado en Problemas (ABP) incluyendo tutorías y prácticas de campo, apoyada en estrategias no presenciales como foro de debate, recursos on-line, cuestionarios y tareas de autoevaluación a través de la plataforma Moodle del Campus Virtual de la UB. Se evalúan asimismo los resultados académicos y las respuestas de los estudiantes a las encuestas realizadas en relación al sistema de impartición de la asignatura. [eng] The pharmaceutical compounding, one of the most representative professional activities of pharmacists, involves the preparation of an individualized medicine tailored to a specific patient in a professional commitment to solve a specific health problem, according to a prescription. The wide range of industrial medicine has significantly reduced this activity, which nevertheless should be considered a tool of the future in line with the current trend of personalizing medicine and patient needs. The knowledge and competences required for this professional activity are introduced to the students of Pharmacy through an optional subject. In this paper we present the ethodological approach developed for this subject by the Teaching Innovation Group of pharmaceutical Technology (GIDTF) and e-Galenica group, both from the University of Barcelona. This methodology is based on Problem-Based Learning (PBL) including tutorials and practices in other centres, supported by out of class strategies as discussion forum, online resources, self-assessment questionnaires and work through the platform Moodle of Virtual Campus UB. The academic performance and student responses to surveys in relation to the didactic methodology are also assessed.

Fostering Collaborative Knowledge Building by the Effective Provision of Knowledge about the Discussion Process

Peer-reviewed

Diseño de aplicativos de "autodiagnóstico sectoriales" como soporte del trabajo autónomo en el nuevo EEES

El objetivo de estos aplicativos, centrados cada uno de ellos en diferentes sectores de la economía, es facilitar la consecución de uno de los objetivos vinculados a la implantación del Espacio Europeo de Enseñanza Superior (EEES), donde se establece que el proceso formativo universitario debe basarse en desarrollar el estudio continuado y autónomo de los estudiantes (self-regulated/managed learning). Nuestro aplicativo informático es un instrumento mediante el cual el alumno, de forma autónoma, puede autoevaluar cuál es su nivel de conocimiento de los contenidos de las asignaturas de Estadística (grado de A.D.E. de la Universitat de Barcelona) a través del análisis de una empresa ubicada en un determinado sector económico. En este sentido, también puede entenderse como un material didáctico en la línea del llamado aprendizaje basado en problemas (problem-based learning). Con una estructura dinámica, basada en cuestiones de opción múltiple, e incorporada como módulo dentro de la plataforma Moodle (utilizada por la Universitat de Barcelona), permite una ejecución "on-line" de su contenido. Nuestra herramienta es un ejemplo más de cómo el uso de las nuevas tecnologías de la información y la comunicación (TIC), puede contribuir enormemente a la innovación de los procesos de enseñanza-aprendizaje en el contexto universitario1

La promoción del pensamiento crítico en el Aprendizaje Basado en Problemas (ABP). Un análisis a partir de los instrumentos de medición

[spa] La literatura científica sobre el Aprendizaje Basado en Problemas (ABP) ha dedicado una atención creciente a la cuestión del pensamiento crítico a lo largo de las dos últimas décadas. Los trabajos de investigación que se han llevado a cabo en los distintos contextos disciplinares de la educación superior presentan definiciones e instrumentos de medición del pensamiento crítico dispares. El presente artículo parte de dicha apreciación y trata de revisar sistemáticamente los mencionados trabajos con un doble objetivo: por un lado, esbozar una clasificación de los instrumentos de medición del pensamiento crítico de estudiantes de ABP y, por el otro, mostrar una panorámica de las evidencias hasta ahora obtenidas; todo ello con la finalidad de animar a profesores, estudiosos y autoridades académicas a seguir avanzando en esta línea de investigación. [eng] Critical thinking has received growing attention from scientific literature on Problem-Based Learning (PBL)during the last two decades. The research carried out in different disciplinary contexts of higher education presents disparate definitions and measuring instruments of critical thinking. This article aims to review systematically the mentioned literature with a dual purpose: on the one hand, to outline a classification of instruments measuring PBL students' critical thinking, on the other, to show an overview of the evidence so far obtained; all of this with the ultimate purpose of encouraging teachers, scholars and academical authorities to proceed further in this line of research.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Hållpunkter för lärande : småbarns möten

Developed from human activities, mathematical knowledge is bound to the world and cultures that men and women experience. One can say that mathematics is rooted in humans’ everyday life, an environment where people reach agreement regarding certain “laws” and principles in mathematics. Through interaction with worldly phenomena and people, children will always gain experience that they can then in turn use to understand future situations. Consequently, the environment in which a child grows up plays an important role in what that child experiences and what possibilities for learning that child has. Variation theory, a branch of phenomenographical research, defines human learning as changes in understanding and acting towards a specific phenomenon. Variation theory implies a focus on that which it is possible to learn in a specific learning situation, since only a limited number of critical aspects of a phenomenon can be simultaneously discerned and focused on. The aim of this study is to discern how toddlers experience and learn mathematics in a daycare environment. The study focuses on what toddlers experience, how their learning experience is formed, and how toddlers use their understanding to master their environment. Twenty-three children were observed videographically during everyday activities. The videographic methodology aims to describe and interpret human actions in natural settings. The children are aged from 1 year, 1 month to 3 years, 9 months. Descriptions of the toddlers’ actions and communication with other children and adults are analyzed phenomenographically in order to discover how the children come to understand the different aspects of mathematics they encounter. The study’s analysis reveals that toddlers encounter various mathematical concepts, similarities and differences, and the relationship between parts and whole. Children form their understanding of such aspects in interaction with other children and adults in their everyday life. The results also show that for a certain type of learning to occur, some critical conditions must exist. Variation, simultaneity, reasonableness and fixed points are critical conditions of learning that appear to be important for toddlers’ learning. These four critical conditions are integral parts of the learning process. How children understand mathematics influences how they use mathematics as a tool to master their surrounding world. The results of the study’s analysis of how children use their understanding of mathematics shows that children use mathematics to uphold societal rules, to describe their surrounding world, and as a tool for problem solving. Accordingly, mathematics can be considered a very important phenomenon that children should come into contact with in different ways and which needs to be recognized as a necessary part of children’s everyday life. Adults working with young children play an important role in setting perimeters for children’s experiences and possibilities to explore mathematical concepts and phenomena. Therefore, this study is significant as regards understanding how children learn mathematics through everyday activities.

Lifelong learning travels : single actors´ perception and talk of lifelong learning in a specific organizational context

I mars 2003 certifierades en finländsk advokatbyrå av den Europeiska kommissionen som den bästa i Europa inom specialkategorin livslångt lärande. Advokatbyrån var överraskad över utnämningen emedan de inte aktivt och/eller medvetet implementerat eller utövat en livslångt lärandestrategi i sin verksamhet bland sin personal. Byrån deltog i en tävling om bästa arbetsplats i Europa ("Best workplaces in Europe 2003") utan att vara medveten om den Europeiska kommissionens special- kategorier. Emedan advokatbyrån inte medvetet implementerat en livslångt lärandestrategi bland sin personal formar aktörerna, vars uppfattning och prat denna avhandling handlar om, sina föreställningar och sitt prat om livslångt lärande efter utnämningen. Översättningsprocessen av en idé utlöses sålunda i denna studie av en extern händelse. I sin avhandling beskriver Annica Isacsson hur och varför en idé (livslångt lärande) föds (på nytt) på en institutionell nivå, hur idén reser och förändras i en process av översättning, hur idén landar i två organisationer samt hur idén om livslångt lärande uppfattas och beskrivs av lokala aktörer i två olika organisationer. Fokus i studien ligger sålunda på enskilda aktörers uppfattning om ett kontroversiellt koncept i en lokal kontext. Teoretiskt möts och sammanlänkas teori om livslångt lärande, sociokulturella teorier om lärande och teorier om organisatoriskt lärande. Isacssons avhandling visar på hur livslångt lärande inte enbart, i en organisatorisk kontext, handlar om individuell kompetensutveckling utan också om organisatoriskt lärande i vilken lärande av andra organisationsmedlemmar och organisationer ingår. Studien visar vidare på hur enskilda aktörers prat påverkas av det institutionella fältet och av den tidsanda inom vilken diskursen livslångt lärande föds, rör sig och ingår.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Organizational learning from customer interaction

In the fierce competition of today‟s business world an organization‟s capacity to learn maybe its only competitive advantage. This research aims at increasing the understanding on how organizational learning from the customer happens in technology companies. In doing so it provides a synthesized definition of organizational learning and investigates processes of organizational learning within technology companies. A qualitative research method and in-depth interviews with different sized high technology companies, as applied here, enables in-depth study of the learning processes. Research contributes to the understanding of what type of knowledge firms acquire, how new knowledge is transferred and used in a learning firm‟s routines and processes. Research findings show that SMEs and large size companies also, depending on their position in the software value chain, consider different knowledge types as most important and that they use different learning methods to acquire knowledge from their customers.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Reverse osmosis membrane surface modification: effects on membrane performance

The aim of this thesis was to study the surface modification of reverse osmosis membranes by surfactants and the effect of modification on rejection and flux. The surfactants included anionic and nonionic surfactants. The purpose of membrane modification was to improve pure water permeability with increasing salt rejection. The literature part of the study deals with the basic principles of reverse osmosis technology and factors affecting the membrane performance. Also the membrane surface modification by surfactants and their influence on membrane’s surface properties and efficiency (permeability and salt rejection) were discussed. In the experimental part of the thesis two thin-film composite membranes, Desal AG and LE-4040, were modified on-line with three different surfactants. The effects of process parameters (pressure, pH, and surfactant concentration) on surface modification were also examined. The characteristics of the modified membranes were determined by measuring the membranes’ contact angle and zeta potentials. The zeta potential and contact angle measurements indicate that the surfactants were adsorbed onto the both membranes. However, the adsorption did not effect on membrane’s pure water permeability and salt rejection. Thereby, the surface modification of the Desal AG and LE-4040 membranes by surfactants was not able to improve the membrane’s performance.