The role of causal links in performance measurement models

Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis and synthesis of the literature from managerial accounting, organizational theory, strategic management and social scientific causal modelling. Findings: The analysis indicates that dynamic, complex and uncertain environments may challenge any reliance upon valid causal models. Due to cognitive limitations and judgmental biases, managers may fail to trace correct cause-and-effect understanding of the value creation in their organizations. However, even lacking this validity, causal models can support strategic learning and perform as organizational guides if they are able to mobilize managerial action. Research limitations/implications: Future research should highlight the characteristics necessary for elaboration of convincing and appealing causal models and the social process of their construction. Practical implications: Managers of organizations using causal models should be clear on the purposes of their particular models and their limitations. In particular, difficulties are observed in specifying detailed cause and effect relations and their potential for communicating and directing attention. They should therefore construct their models to suit the particular purpose envisaged. Originality/value: This paper provides an interdisciplinary and holistic view on the issue of causality in managerial accounting models.

Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

What can ecosystems learn? Expanding evolutionary ecology with learning theory.

BACKGROUND: The structure and organisation of ecological interactions within an ecosystem is modified by the evolution and coevolution of the individual species it contains. Understanding how historical conditions have shaped this architecture is vital for understanding system responses to change at scales from the microbial upwards. However, in the absence of a group selection process, the collective behaviours and ecosystem functions exhibited by the whole community cannot be organised or adapted in a Darwinian sense. A long-standing open question thus persists: Are there alternative organising principles that enable us to understand and predict how the coevolution of the component species creates and maintains complex collective behaviours exhibited by the ecosystem as a whole? RESULTS: Here we answer this question by incorporating principles from connectionist learning, a previously unrelated discipline already using well-developed theories on how emergent behaviours arise in simple networks. Specifically, we show conditions where natural selection on ecological interactions is functionally equivalent to a simple type of connectionist learning, 'unsupervised learning', well-known in neural-network models of cognitive systems to produce many non-trivial collective behaviours. Accordingly, we find that a community can self-organise in a well-defined and non-trivial sense without selection at the community level; its organisation can be conditioned by past experience in the same sense as connectionist learning models habituate to stimuli. This conditioning drives the community to form a distributed ecological memory of multiple past states, causing the community to: a) converge to these states from any random initial composition; b) accurately restore historical compositions from small fragments; c) recover a state composition following disturbance; and d) to correctly classify ambiguous initial compositions according to their similarity to learned compositions. We examine how the formation of alternative stable states alters the community's response to changing environmental forcing, and we identify conditions under which the ecosystem exhibits hysteresis with potential for catastrophic regime shifts. CONCLUSIONS: This work highlights the potential of connectionist theory to expand our understanding of evo-eco dynamics and collective ecological behaviours. Within this framework we find that, despite not being a Darwinian unit, ecological communities can behave like connectionist learning systems, creating internal conditions that habituate to past environmental conditions and actively recalling those conditions. REVIEWERS: This article was reviewed by Prof. Ricard V Solé, Universitat Pompeu Fabra, Barcelona and Prof. Rob Knight, University of Colorado, Boulder.

Microquasar models for 3EG J1828+0142 and 3EG J1735-1500

Microquasars are promising candidates to emit high-energy gamma-rays. Moreover, statistical studies show that variable EGRET sources at low galactic latitudes could be associated with the inner spiral arms. The variable nature and the location in the Galaxy of the high-mass microquasars, concentrated in the galactic plane and within 55 degrees from the galactic center, give to these objects the status of likely counterparts of the variable low-latitude EGRET sources. We consider in this work the two most variable EGRET sources at low-latitudes: 3EG J1828+0142 and 3EG J1735-1500, proposing a microquasar model to explain the EGRET data in consistency with the observations at lower energies (from radio frequencies to soft gamma-rays) within the EGRET error box.

Older people's university students in Spain: a comparison of motives and benefits between two models

This study examines both the motives for and the benefits of attending a uni- versity programme for older people (UPOP) in Spain, and how they vary with the type of UPOP. Two UPOP models were assessed: The"Older People"s Classes" of the University of Barcelona, which is organised as a lecture course, and the"University of Experience" at the University of Valencia, which is a three- or four- year variant of regular university degrees. A sample of 321 older students (mean age 67.5 years) was gathered from the two UPOPs, 161 participants from the former and 157 from the latter. The findings suggest that expressive motives such as acquiring knowledge, expanding the mind or learning for the joy of learning were the most important reasons for joining a UPOP, and that among the perceived benefits from taking classes at university featured"gaining more friends","enhanced self or life-satisfaction" and"joy in life". Perceived benefits were particularly high among the less educated and the older students. While students participating in the Older People"s Classes were older and included relatively more women, differences between the two models in motives and benefits did not exist or were slight. These results are discussed in the context of new strategies to improve university courses aimed at older students.

Feedback-related Brain Potential Activity Complies with Basic Assumptions of Associative Learning Theory

Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cueoutcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cueoutcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models. ■

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.

Conditions for EFL learning and professional development : Finland-Swedish learner and teacher perspectives

Engelskans dominerande roll som internationellt språk och andra globaliseringstrender påverkar också Svenskfinland. Dessa trender påverkar i sin tur förutsättningarna för lärande och undervisning i engelska som främmande språk, det vill säga undervisningsmålen, de förväntade elev- och lärarroller, materialens ändamålsenlighet, lärares och elevers initiala erfarenheter av engelska och engelskspråkiga länder. Denna studie undersöker förutsättningarna för lärande och professionell utveckling i det svenskspråkiga nybörjarklassrummet i engelska som främmande språk. Utgångsläget för 351 nybörjare i engelska som främmande språk och 19 av deras lärare beskrivs och analyseras. Resultaten tyder på att engelska håller på att bli ett andraspråk snarare än ett traditionellt främmande språk för många unga elever. Dessa elever har också goda förutsättningar att lära sig engelska utanför skolan. Sådan var dock inte situationen för alla elever, vilket tyder på att det finns en anmärkningsvärd heterogenitet och även regional variation i det finlandssvenska klassrummet i engelska som främmande språk. Lärarresultaten tyder på att vissa lärare har klarat av att på ett konstruktivt sätt att tackla de förutsättningar de möter. Andra lärare uttrycker frustration över sin arbetssituation, läroplanen, undervisningsmaterialen och andra aktörer som kommer är av betydelse för skolmiljön. Studien påvisar att förutsättningarna för lärande och undervisning i engelska som främmande språk varierar i Svenskfinland. För att stöda elevers och lärares utveckling föreslås att dialogen mellan aktörer på olika nivå i samhället bör förbättras och systematiseras.

Enhancing human security through crisis management : opportunities and challenges for learning

Inhimilliseen turvallisuuteen kriisinhallinnan kautta – oppimisen mahdollisuuksia ja haasteita Kylmän sodan jälkeen aseelliset konfliktit ovat yleensä alkaneet niin sanotuissa hauraissa valtioissa ja köyhissä maissa, ne ovat olleet valtioiden sisäisiä ja niihin on osallistunut ei-valtiollisia aseellisia ryhmittymiä. Usein ne johtavat konfliktikierteeseen, jossa sota ja vakaammat olot vaihtelevat. Koska kuolleisuus konflikteissa voi jäädä alle kansainvälisen määritelmän (1000 kuollutta vuodessa), kutsun tällaisia konflikteja ”uusiksi konflikteiksi”. Kansainvälinen yhteisö on pyrkinyt kehittämään kriisinhallinnan ja rauhanrakentamisen malleja, jotta pysyvä rauhantila saataisiin aikaiseksi. Inhimillinen turvallisuus perustuu näkemykseen, jossa kunnioitetaan jokaisen yksilön ihmisoikeuksia ja jolla on vaikutusta myös kriisinhallinnan ja rauhanrakentamisen toteuttamiseen. Tutkimukseen kuuluu kaksi empiiristä osaa: Delfoi tulevaisuuspaneeliprosessin sekä kriisinhallintahenkilöstön haastattelut. Viisitoista eri alojen kriisinhallinta-asiantuntijaa osallistui paneeliin, joka toteutettiin vuonna 2008. Paneelin tulosten mukaan tulevat konfliktit usein ovat uusien konfliktien kaltaisia. Lisäksi kriisinhallintahenkilöstöltä edellytetään vuorovaikutus- ja kommunikaatiokykyä ja luonnollisesti myös varsinaisia ammatillisia valmiuksia. Tulevaisuuspaneeli korosti vuorovaikutus- ja kommunikaatiotaitoja erityisesti siviilikriisinhallintahenkilöstön kompetensseissa, mutta samat taidot painottuivat sotilaallisen kriisinhallinnan henkilöstön kompetensseissakin. Kriisinhallinnassa tarvitaan myös selvää työnjakoa eri toimijoiden kesken. Kosovossa työskennelleen henkilöstön haastatteluaineisto koostui yhteensä 27 teemahaastattelusta. Haastateltavista 9 oli ammattiupseeria, 10 reservistä rekrytoitua rauhanturvaajaa ja 8 siviilikriisinhallinnassa työskennellyttä henkilöä. Haastattelut toteutettiin helmi- ja kesäkuun välisenä aikana vuonna 2008. Haastattelutuloksissa korostui vuorovaikutus- ja kommunikaatiotaitojen merkitys, sillä monissa käytännön tilanteissa haastateltavat olivat ratkoneet ongelmia yhteistyössä muun kriisinhallintahenkilöstön tai paikallisten asukkaiden kanssa. Kriisinhallinnassa toteutui oppimisprosesseja, jotka usein olivat luonteeltaan myönteisiä ja informaalisia. Tällaisten onnistumisten vaikutus yksilön minäkuvaan oli myönteinen. Tällaisia prosesseja voidaan kuvata ”itseä koskeviksi oivalluksiksi”. Kriisinhallintatehtävissä oppimisella on erityinen merkitys, jos halutaan kehittää toimintoja inhimillisen turvallisuuden edistämiseksi. Siksi on tärkeää, että kriisinhallintakoulutusta ja kriisinhallintatyössä oppimista kehitetään ottamaan huomioon oppimisen eri tasot ja ulottuvuudet sekä niiden merkitys. Informaaliset oppimisen muodot olisi otettava paremmin huomioon kriisinhallintakoulutusta ja kriisinhallintatehtävissä oppimista kehitettäessä. Palautejärjestelmää olisi kehitettävä eri tavoin. Koko kriisinhallintaoperaation on saatava tarvittaessa myös kriittistä palautetta onnistumisista ja epäonnistumisista. Monet kriisinhallinnassa työskennelleet kaipaavat kunnollista palautetta työrupeamastaan. Liian rutiininomaiseksi koettu palaute ei edistä yksilön oppimista. Spontaanisti monet haastatellut pitivät tärkeänä, että kriisinhallinnassa työskennelleillä olisi mahdollisuus debriefing- tyyppiseen kotiinpaluukeskusteluun. Pelkkä tällainen mahdollisuus ilmeisesti voisi olla monelle myönteinen uutinen, vaikka tilaisuutta ei hyödynnettäisikään. Paluu kriisinhallintatehtävistä Suomeen on monelle haasteellisempaa kuin näissä tehtävissä työskentelyn aloittaminen ulkomailla. Tutkimuksen tulokset kannustavat tutkimaan kriisinhallintaa oppimisen näkökulmasta. On myös olennaista, että kriisinhallinnan palautejärjestelmiä kehitetään mahdollisimman hyvin edistämään sekä yksilöllistä että organisatorista oppimista kriisinhallinnassa. Kriisinhallintaoperaatio on oppimisympäristö. Kriisinhallintahenkilöstön kommunikaatio- ja vuorovaikutustaitojen kehittäminen on olennaista tavoiteltaessa kestävää rauhanprosessia, jossa konfliktialueen asukkaatkin ovat mukana.

Low-fidelity bench models for basic surgical skills training during undergraduate medical education

It is remarkable the reduction in the number of medical students choosing general surgery as a career. In this context, new possibilities in the field of surgical education should be developed to combat this lack of interest. In this study, a program of surgical training based on learning with models of low-fidelity bench is designed as a complementary alternative to the various methodologies in the teaching of basic surgical skills during medical education, and to develop personal interests in career choice.

Learning Grasp Affordances from Vision

Monimutkaisissa ja muuttuvissa ympäristöissä työskentelevät robotit tarvitsevat kykyä manipuloida ja tarttua esineisiin. Tämä työ tutkii robottitarttumisen ja robottitartuntapis-teiden koneoppimisen aiempaa tutkimusta ja nykytilaa. Nykyaikaiset menetelmät käydään läpi, ja Le:n koneoppimiseen pohjautuva luokitin toteutetaan, koska se tarjoaa parhaan onnistumisprosentin tutkituista menetelmistä ja on muokattavissa sopivaksi käytettävissä olevalle robotille. Toteutettu menetelmä käyttää intensititeettikuvaan ja syvyyskuvaan po-hjautuvia ominaisuuksi luokitellakseen potentiaaliset tartuntapisteet. Tämän toteutuksen tulokset esitellään.

Rising to the impossible challenge: the storage of all research data, forever?

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