Orientador: Takaaki Ohishi / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-08T10:06:35Z (GMT). No. of bitstreams: 1 LeoneFilho_MarcosdeAlmeida_M.pdf: 1557959 bytes, checksum: 92dc63d4e3140cc61ba7900961c0e9fb (MD5) Previous issue date: 2006 / Resumo: Neste trabalho é proposta uma metodologia para previsão de séries temporais de carga de energia elétrica de curto prazo. Esta metodologia vem sendo muito utilizada no contexto da previsão de séries temporais e do reconhecimento de padrões. Os autores que propuseram esta metodologia a chamaram de "Ensembles". Este nome tenta explicar o é este modelo: uma combinação de partes que juntas formam um só modelo. Neste sentido, este nome expressa com relativa clareza qual é o principal aspecto desta metodologia, que no caso específico deste trabalho, é o de fazer várias previsões de uma mesma série temporal utilizando diferentes ferramentas que sozinhas são suficientemente competentes para prever a série temporal em questão, e em seguida combinar as soluções para, deste modo, tentar obter uma solução melhor do que quando é usada somente uma ferramenta. As ferramentas usadas para compor a previsão dos "Ensembles" finais são Redes Neurais Artificiais (RNAs) e Redes Neurais Nebulosas. Atualmente, estas redes são largamente utilizadas em problemas de previsão de séries temporais, principalmente quando o fator gerador destas séries é um sistema não-linear. Desta forma, isto as tornou candidatas potenciais para prever valores de uma série de cargas de energia elétrica, pois este tipo de série tem características essencialmente não-lineares. Sendo assim, foram utilizados quatro tipos de redes: RNAs MLPs, RNAs Recorrentes, RNAs de Base Radial e Redes Neurais Nebulosas tipo ANFIS. Com os modelos básicos de redes foram, utilizados Algoritmos Genéticos para evoluir os parâmetros destas redes e, assim, chegar a uma população de redes suficientemente competentes para fazer as previsões da série de cargas. Na próxima etapa, com os resultados das previsões da população de redes evoluídas foi feita a seleção dos melhores agrupamentos destas redes evoluídas e, como este processo requer a avaliação de diferentes configurações de modelos, esta seleção é baseada em Algoritmos Genéticos.Os resultados obtidos ao se utilizar "ensembles" mostraram que este modelo foi capaz de alcançar uma grande robustez na previsão, reduzindo os erros de previsão, suavizando os resultados de previsão e deixando o modelo menos suscetível a grandes erros quando surgem "outliers" no conjunto de dados / Abstract: This work proposes a methodology for short-term electric power load forecasting. This methodology is being widely used under the context of time series prediction and pattern recognition. It was named "ensembles" by the authors who developed it. This name carries the meaning of an assemblage of parts considered as forming a whole. Therefore, this name expresses rather clearly the main characteristic of this methodology, which under the framework of this study is to make several predictions of the same time series using various different tools in which every single one alone is sufficiently competent to predict the above mentioned time series. After that, the predictions are combined in order to achieve a better prediction compared to the one that is obtained if a single predictor is used. The tools implemented to form the final "ensembles" prediction are Artificial Neural Networks (ANNs) and Neuro-fuzzy Networks. Nowadays, these networks are being widely used in time series predictions problems, mainly when the factor that generates these series is a non-linear system. Hence, this fact has elected them as potential candidates to predict future values of an electric power load series because this series has essentially non-linear characteristics. As a result, four types of networks were utilized in this work: MLPs ANNs, Recurrent ANNs, Radial Basis ANNs and ANFIS type Neuro-fuzzy networks. So, with the basic networks models, Genetic Algorithms were applied to evolve the parameters of these networks and, as a consequence, a population of networks sufficiently capable of predicting future values of the load time series was built. On the next step, with the results obtained from the evolved population of networks, a selection of the most suitable results of the individual networks were made and, as soon as this process implies the evaluation of multiple different combinations of models, this methodology was based on Genetic Algorithms. Then, this selected networks were combined. The results when using "ensembles" revealed that this model was able to reach a great robustness in prediction tasks. In that sense, it was possible to reduce the level of prediction error, to smooth the resulting predictions and to make the model more stable reducing the possibilities of presenting high levels of errors when the used data set contains "outliers" / Mestrado / Energia Eletrica / Mestre em Engenharia Elétrica

La gravité du traumatisme crânien (TC) dépend de la sévérité immédiate des lésions primaires mais également de leur aggravation dans les heures et les jours qui suivent le TC, avec l’apparition de lésions secondaires. La neuro-inflammation constitue l’une des cascades physiopathologiques post-TC dont le contrôle a été décrit comme une stratégie neuroprotectrice potentielle. Elle compromet le taux de la forme soluble α du précurseur du peptide ß amyloÏde, sAPPα, un neuroprotecteur endogène issu de l’action des enzymes α-sécrétases (ADAMs). Dans ce contexte, mon travail de thèse a eu pour but d’étudier l’intérêt thérapeutique des composés pharmacologiques modulant le taux de sAPPα post-TC sur les conséquences biochimiques, histopathologiques et fonctionnelles, à court et à long terme, dans un modèle de TC par percussion mécanique chez la souris. Parmi les différents composés, la minocycline, une tetracycline de 2e génération aux effets anti-inflammatoires, et l’étazolate, une pyrazolopyridine récemment décrite comme activateur des α-sécrétases, ont été sélectionnés. Le traitement anti-inflammatoire par la minocycline permet de restaurer le taux de la sAPPα, et cet effet dans la phase précoce est accompagné d’une réduction des conséquences histopathologiques (atrophie callosale et striatale, lésion des bulbes olfactifs et ventriculomégalie) à 3 mois post-TC. Sur le plan fonctionnel, le test d’aversion olfactive a été pour la première fois mis au point sur un modèle expérimental de TC et a permis de révéler un déficit olfactif persistant dans notre modèle. De plus, un déficit cognitif persistant a été également mis en évidence par le test NORT « Novel Object Recognition Test ». Le même traitement par la minocycline a permis de corriger ces déficits olfactif et cognitif à court et à long terme (3 mois) post-TC. Les résultats obtenus sur l’étazolate (étude de fenêtre thérapeutique, étude d’effet-dose) ont montré, pour la première fois dans un modèle de lésion cérébrale, son potentiel anti-inflammatoire et anti-œdémateux, associé à la restauration du taux de la sAPPα, avec une fenêtre thérapeutique d’au moins de 2h. Le même traitement réduit les conséquences histopathologiques (activation microgliale, ventriculomégalie, lésion des bulbes olfactives) et fonctionnelles (hyperactivité locomotrice, déficit cognitif), à court à long terme (3 mois) post-TC. En conclusion, l’ensemble de ce travail a permis d’établir les bénéfices d’une stratégie pharmacologique s’opposant à la fois à la neuro-inflammation et à la chute du taux de la sAPPα dans la phase précoce de TC avec une amélioration histologique et fonctionnelle à long terme, soulignant son intérêt thérapeutique. Il est important de souligner que la minocycline est déjà entrée en essai clinique pour le traitement de TC, et que malgré le peu de données précliniques, l’étazolate (EHT-0202) est tout récemment entré en phase II pour le traitement de la maladie d’Alzheimer. / The severity of the sequelae of traumatic brain injury (TBI) depends on the extent of primary damage as well as the implication of secondary injury cascades that are triggered within the hours and days post- insult. Neuroinflammation is an important post-TBI cascade whose inhibition has been described as a potential neuroprotective strategy. Neuroinflammation has been associated to the decrease of an endogenous neuroprotector, the soluble form α of the amyloid precursor protein (sAPPα), generated by the activity of the enzymes α-secretases or ADAMs. The aim of this work was to evaluate the therapeutic interest of pharmacological compounds that restore sAPPα levels on short- and long-term biochemical, histological and functional outcome in a mouse model of TBI by mechanical percussion. Among the potential candidates, the compounds selected were minocycline, a tetracycline that exerts anti-inflammatory activity, and etazolate, a pyrazolopyridine that activates α-secretases. The anti-inflammatory treatment with minocycline was able to restore post-TBI sAPPα levels, and this acute effect was accompanied by lasting neuroprotection, namely reduction of lesion size (corpus callosum, striatum and olfactory bulbs) and ventriculomegaly and attenuation of glial reactivity. The olfactory aversion test, developped for the first time in experimental TBI, unraveled a persistant olfactory deficit. Moreover, a durable cognitive deficit was revealed by the Novel Object Recognition Task (NORT). Treatment with minocycline was able to attenuate both the olfactory and cognitive deficits in an effective manner. Moreover, the results obtained in the pharmacological study with etazolate (therapeutic window, dose-response) demonstrated, for the very first time, the anti-inflammatory and anti-oedematous efficacy of etazolate, when administered at least 2 hours post-TBI. The same treatment protocol was also able to attenuate sAPPα levels and offered persistent neuroprotection, namely reduction of lesion size (ventriculomegaly, olfactory bulb lesion) and microglial activation, and attenuation of functional deficits (hyperactivity, cognitive deficit). In conclusion, the findings of this work highlight the therapeutic efficacy of compounds that attenuate neuroinflammation and restore sAPPa levels within the acute and critical post-TBI aftermath, on histological and functional outcome. It is worth noting that minocycline is actually in a clinical trial for the treatment of traumatic brain injury and etazolate (EHT 0202), despite the poor experimental data available, has managed to enter a clinical trial for the treatment of Alzheimer’s disease.

This thesis charts the developments that have occurred in the field of managerial education specifically from the perspective of the current trends in educational programmes both in the Czech Republic as well as abroad. The theoretical section of the thesis consists of a pilot study aimed at the demand for educational and developmental programmes amongst a selected research sample of managers and also at an analysis of the supply offered by a sample of educational organisations located in the City of Prague. Based on the information that was gathered, certain conclusions were drawn and recommendations made for modifying the study programmes offered by the Faculty of Management of the University of Economics.

Dans ce projet nous nous intéresserons à la création d’un nouveau modèle permettant de simuler des enregistrements extracellulaires de l’activité électrique neurale dans le système nerveux périphérique. Ce modèle fut développé pour permettre une meilleure compréhension de l’impact des différentes propriétés des interfaces sur la qualité des signaux recueillis. Ce projet fut en particulier conduit pour répondre au contexte actuel qui voit le développement de nombreuses applications dans le domaine des neuro-prothèses et autres interfaces neurales à but biomédical. Nos intentions étaient de fournir un nouvel outil permettant de mieux comprendre les particularités des interfaces existantes ou d’aider à leur amélioration et à la planification de futures innovations. Ce modèle est construit comme la synthèse de la compréhension actuelle des différents rouages biophysiques impactant les enregistrements. Sa structure peut être perçue comme l’assemblage de différents sous-systèmes interconnectés et représentant chacun une dimension du processus. Il s’avère particulièrement efficace pour l’analyse comparative des performances entre diffèrent types/géométries d’électrodes invasives. Dans ce document, nous nous efforcerons d’expliquer en détail la structure et les paramètres de notre modèle. Nous décrirons ensuite les différents tests que nous avons entrepris pour sa validation expérimentale, ainsi que les différentes voies d’applications que nous avons commencé à explorer. Nous finirons par décrire les améliorations qui nous sont apparues comme nécessaires ou possibles et par une discussion sur les ouvertures futures offerte à ce domaine de recherche. / Neural interfaces are becoming a newly dynamic and promising field especially thanks to the numerous applications they could have in the biomedical domain. A great deal of these applications requires a monitoring of targeted neural activity. Among the different technologies available for such recording practice, chronic electrodes implanted in the peripheral nervous system offer a good compromise on the resolution versus invasiveness technological constraint. A large array of electrodes has been developed in this intention but there is still only a limited comprehension of their recording principles and weakness. This makes difficult any targeted improvement of the electrodes and led this field to be mainly dominated by a trial and error empirical approach simultaneously costly in funds, animal lives and time. In particular, intrafascicular electrodes, while providing exiting results for stimulation, have often failed in recordings. These electrodes typically show interesting recording performance right after implantation but have rapid decline of their efficacy up to the points that they often become useless after a few weeks. Such performance proves problematic as they drastically limit the transfer of experimental results to human applications. The extent of our work has been the development of a theoretical framework for the study of implantable electrodes. Our goal here has been to construct a model that could be used as a platform to better understand implanted electrode and compare their performance and possible improvement. We focused our work on intrafascicular electrode for the peripheral nervous system. However, our procedure could easily be applied to other type of interface. During this project we first constructed a detailed model of the recording biophysical process happening at the peripheral nerve electrical interface. This model encompasses all the mechanism known to influence the quality and shape of neural activity recordings. We have then recreated within our model specific controlled experiments and by comparing the properties of the simulated recording with their experimental counterparts demonstrated the potency of our approach to produce bio-plausible signals. This validated our model as an in silico alternative to compare and test electrodes. We then further developed this model to also simulate some of the changes happening in the nerve post implantation. In particular, we found that the growth of the fibrotic scar could already explain a large part of the signal degradation happening in the first weeks. Then to demonstrate the adaptability of this model we used it to compare the performance of the main type of electrodes implanted nowadays peripherally. Finally, as the main weakness of our model relied in its relative complexity and the related long computing time, we started to analyze how this model could be simplified without losing the precision necessary for the intended applications. In conclusion, this project led to the creation of a model which in its current form can be used as an in silico platform to test and compare electrodes. This will facilitate the planning and development of future peripheral neural interface by proving both more economical and informative that current strategies. Conjointly, we opened the way to future improvement of our model, leading to more practicality.

The intention of this study was theory creation in the field of organisational change, directed towards the creation of a conceptual change framework. A qualitative research approach was followed and a grounded theory methodology adopted. This study involved a theoretical investigation of organisational change and leadership within South African organisations, although insights gained could be transferred across contexts or settings. The primary aim was to create a practical change framework to ensure sustainable organisational change. Secondly, to determine the impact of leadership on successful organisational change. Thirdly, to establish whether any fundamental elements can be identified as essential for inclusion in such a change framework. Fourthly, to identify non-negotiable success factors that can ensure successful change. Fifthly, to determine the human elements that should be included in order to minimise negative outcomes such as resistance and noncompliance. The final aim was to ascertain what meta-insights can be gained from organisational change and leadership. The research findings concluded that the first perception when speaking about change is fear, anxiety and increased stress, resulting in impaired functioning. Organisations struggle to handle increased stress levels during periods of change and require improved methods of dealing with stress to ensure optimal individual functioning. Only through reduced stress levels will individuals be able to engage with organisational change initiatives. Alternative intervention technologies were suggested which could assist the individual change journey through reduced stress and/or increased consciousness. These alternative intervention technologies were suggested because of the paucity of current literature. It practically aids organisations on how to deal with the stress dilemma. This research introduced the concepts of anti-leader and anti-manager. These concepts depict the negative characteristics of leadership and management which invariably increases individual stress levels. Emotions elicited by the anti-leader and/or anti-manager could potentially split, divide and fragment a workforce. The ideal organisational approach should be designed by the people, be inclusive of all, involve, empower and allow individuals to make the required decisions. As organisational change can only be effected through individual change, this thesis places the individual in the centre. Without individual change, vicissitude and sustainable organisational change become highly unlikely. / Graduate School of Business Leadership / DBL

The thesis deals with artificial neural networks theory. Subsequently, fuzzy sets are being described and fuzzy logic is explained. The hybrid neuro-fuzzy system stemming from ANFIS system is designed on the basis of artificial neural networks, fuzzy sets and fuzzy logic. The upper-mentioned systems' functionality has been demonstrated on an inverted pendulum controlling problem. The three controllers have been designed for the controlling needs - the first one is on the basis of artificial neural networks, the second is a fuzzy one, and the third is based on ANFIS system.  The thesis is aimed at comparing the described systems, which the controllers have been designed on the basis of, and evaluating the hybrid neuro-fuzzy system ANFIS contribution in comparison with particular theory solutions. Finally, some experiments with the systems are demonstrated and findings are assessed.

In this thesis, we discuss different techniques to bridge the gap between two different approaches to artificial intelligence: the symbolic and the connectionist paradigm. Both approaches have quite contrasting advantages and disadvantages. Research in the area of neural-symbolic integration aims at bridging the gap between them. Starting from a human readable logic program, we construct connectionist systems, which behave equivalently. Afterwards, those systems can be trained, and later the refined knowledge be extracted.

<p>Language “in the wild” is complex and ambiguous and relies on a shared understanding of the world for its interpretation. Most current natural language processing methods represent language by learning word co-occurrence patterns from massive amounts of linguistic data. This representation can be very powerful, but it is insufficient to capture the meaning behind written and spoken communication. </p> <p> </p> <p>In this dissertation, I will motivate neural-symbolic representations for dealing with these challenges. On the one hand, symbols have inherent explanatory power, and they can help us express contextual knowledge and enforce consistency across different decisions. On the other hand, neural networks allow us to learn expressive distributed representations and make sense of large amounts of linguistic data. I will introduce a holistic framework that covers all stages of the neural-symbolic pipeline: modeling, learning, inference, and its application for diverse discourse scenarios, such as analyzing online discussions, mining argumentative structures, and understanding public discourse at scale. I will show the advantages of neural-symbolic representations with respect to end-to-end neural approaches and traditional statistical relational learning methods.</p> <p><br></p> <p>In addition to this, I will demonstrate the advantages of neural-symbolic representations for learning in low-supervision settings, as well as their capabilities to decompose and explain high-level decision. Lastly, I will explore interactive protocols to help human experts in making sense of large repositories of textual data, and leverage neural-symbolic representations as the interface to inject expert human knowledge in the process of partitioning, classifying and organizing large language resources. </p>

Over the past 60 years, a large number of selective neurotoxins were discovered and developed, making it possible to animal-model a broad range of human neuropsychiatric and neurodevelopmental disorders. In this paper, we highlight those neurotoxins that are most commonly used as neuroteratologic agents, to either produce lifelong destruction of neurons of a particular phenotype, or a group of neurons linked by a specific class of transporter proteins (i.e., dopamine transporter) or body of receptors for a specific neurotransmitter (i.e., NMDA class of glutamate receptors). Actions of a range of neurotoxins are described: 6-hydroxydopamine (6-OHDA), 6-hydroxydopa, DSP-4, MPTP, methamphetamine, IgG-saporin, domoate, NMDA receptor antagonists, and valproate. Their neuroteratologic features are outlined, as well as those of nerve growth factor, epidermal growth factor, and that of stress. The value of each of these neurotoxins in animal modeling of human neurologic, neurodegenerative, and neuropsychiatric disorders is discussed in terms of the respective value as well as limitations of the derived animal model. Neuroteratologic agents have proven to be of immense importance for understanding how associated neural systems in human neural disorders may be better targeted by new therapeutic agents.

Bakgrund: Visuell snö är ett perceptionsstörande neurooftalmologiskt tillstånd karakteriserat av bestående mikroskopiska flimrande prickar som täcker hela det bilaterala synfältet. Det kan liknas vid att titta genom en flimrande tv-skärm, eller Gaussiskt brus. Några etablerade riktlinjer för behandling finns inte för närvarande. Syfte: Denna litteraturstudie syftar till att undersöka tillgänglig litteratur rörande effekten av olika behandlingsalternativ för tillståndet visuell snö.  Metod: En sökning utfördes i sökmotorn PubMed den 20 mars 2023. Söksträngen som användes var “visual snow” OR “visual snow syndrome” AND “treatment”. Fler studier tillkom genom granskning av referenser. Begränsningar i urvalet baserades på relevans rörande behandling, samt en litteraturstudie utförd av Eren &amp; Schankin publicerad 2020. Den här studien tar upp arbeten tillkomna därefter, totalt 8 artiklar utgivna mellan 2020-2022.  Resultat: Vår studie har lyckats identifiera behandlingsalternativ för visuell snö i form av neuro-optometrisk synträning, farmaceutika, kosttillskott, kiropraktik, filterglasögon, antikroppar, mydriatika, synstimuli, samt repetitiv transkraniell magnetstimulering. Samtliga studier utfördes på deltagare med bekräftad och diagnostiserad visuell snö, antingen som isolerat symptom, som del av Visual Snow Syndrome, eller som sekundärt tillstånd. Positiva behandlingssvar med partiell remission förekommer, samt enstaka fall av total remission. Samtliga inkluderade studier har sina begränsningar, en gemensam sådan är svårigheten att kvantifiera symptomen. Med hjälp av enkäter och symptomdagböcker har 7 av 8 studier visat på viss subjektiv effekt av behandling, av okänd magnitud.  Slutsats: Patofysiologin bakom visuell snö är ännu inte klarlagd. I dagsläget finns ingen generellt applicerbar behandling för visuell snö, men enstaka fall av total remission samt ett antal fall av partiell remission förekommer i litteraturen. Vid behandling av patienter med visuell snö bör hänsyn tas till individuella patienters förutsättningar, komorbiditet och tidigare prövad behandling. / Background: Visual snow is a neuro-ophthalmological perception disorder characterized by persistent microscopic flickering dots covering the bilateral field of vision. It can be described as looking through TV static, or Gaussian noise. There are currently no established guidelines regarding treatment. Purpose: This literature survey aimed to investigate available literature regarding the efficacy of different therapeutic approaches for the condition of visual snow.   Method: A search was performed in the PubMed search engine on March 20, 2023. The search string used was “visual snow” OR “visual snow syndrome” AND “treatment”. Further studies were added through references. Restrictions in article selection were based on relevance regarding treatment, as well as a review by Eren &amp; Schankin published in 2020. This study covers subsequent articles, a total of 8 articles published between 2020-2022. Results: Our study has identified therapeutic approaches to visual snow in the form of neuro-optometric rehabilitation therapy, pharmaceuticals, nutraceuticals, chiropractic treatment, filter glasses, antibodies, mydriatics, visual stimuli, and repetitive transcranial magnetic stimulation. All participants had confirmed and diagnosed visual snow either as an isolated symptom, as part of Visual Snow Syndrome, or as a secondary condition. Positive responses with partial remission occur, as well as occasional total remissions. All included studies have some limitations, a common one being the difficulty in quantifying the symptoms. Using questionnaires and symptom diaries, 7 out of 8 studies have shown some subjective effect of treatment of unknown magnitude.  Conclusion: The pathophysiology behind visual snow is not yet fully understood. Currently, there is no generally applicable treatment for visual snow, but occasional cases of total remission and a number of cases of partial remission appear in the literature. When treating patients with visual snow, the individual patient’s conditions, comorbidity and previously tried treatment should be taken into account.