Dissertations / Theses on the topic 'Classical learning'
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Aschieri, Federico. "Learning, realizability and games in classical arithmetic." Thesis, Queen Mary, University of London, 2011. http://qmro.qmul.ac.uk/xmlui/handle/123456789/2325.
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Abstract. In this dissertation we provide mathematical evidence that the concept of learning can be used to give a new and intuitive computational semantics of classical proofs in various fragments of Predicative Arithmetic. First, we extend Kreisel modi ed realizability to a classical fragment of rst order Arithmetic, Heyting Arithmetic plus EM1 (Excluded middle axiom restricted to 0 1 formulas). We introduce a new realizability semantics we call \Interactive Learning-Based Realizability". Our realizers are self-correcting programs, which learn from their errors and evolve through time, thanks to their ability of perpetually questioning, testing and extending their knowledge. Remarkably, that capability is entirely due to classical principles when they are applied on top of intuitionistic logic. Secondly, we extend the class of learning based realizers to a classical version PCFClass of PCF and, then, compare the resulting notion of realizability with Coquand game semantics and prove a full soundness and completeness result. In particular, we show there is a one-to-one correspondence between realizers and recursive winning strategies in the 1-Backtracking version of Tarski games. Third, we provide a complete and fully detailed constructive analysis of learning as it arises in learning based realizability for HA+EM1, Avigad's update procedures and epsilon substitution method for Peano Arithmetic PA. We present new constructive techniques to bound the length of learning processes and we apply them to reprove - by means of our theory - the classic result of G odel that provably total functions of PA can be represented in G odel's system T. Last, we give an axiomatization of the kind of learning that is needed to computationally interpret Predicative classical second order Arithmetic. Our work is an extension of Avigad's and generalizes the concept of update procedure to the trans nite case. Trans- nite update procedures have to learn values of trans nite sequences of non computable functions in order to extract witnesses from classical proofs.
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Silkstone, Francis. "Learning Thai classical music : memorisation and improvisation." Thesis, SOAS, University of London, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388511.
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As in other oral traditions, the core of traditional training in Thai classical music is that the student memonses music given by the teacher. Teachers offer few explanations but give musical examples that transmit each skill at the right time for the student. Training on fiddles can be understood by considering three learned elements: Basic Melody: the essential structure of each composition, encapsulated in its most tangible form as the melody played on the large gong-circle, but internalised in increasingly subtle and fluid forms as the student progresses; Realisations of each composition for fiddles, improvised by the teacher and memorised by the student during each lesson; Various techniques of improvisation (ways of realising the Basic Melody of a given composition as a new melody for fiddle). Learning how to conceptualise the Basic Melody is inseparable from gaining competence in fiddle improvisation. Teachers' explanations concerning melodies they teach suggest transmission of a highly flexible conceptualisation of Basic Melody and a complex technique of improvisation. Three etic explanations of the latter are: 'Filling-in': the player inserts notes between the notes of the less dense Basic Melody so that the fiddle melody conforms to each pitch of the Basic Melody. 'Idiomatic elaboration': a fiddle melody is derived from the Basic Melody according to a musical 'grammar' in which every pitch need not conform to the v Basic Melody, though many pitches are likely to do so. Formulaic manipulation: for each Basic Melody formula, the fiddle player chooses one of several eligible fiddle-formulas, then spontaneously adjusts it in a manner appropriate to that context and moment. These three are sometimes alternative explanations of the same process, sometimes distinct processes. In each rendition, a teacher moves between the three processes. All three are necessary to the complexities and beautiful ambiguities of musical thought.
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Jovanovic, Filip, and Paul Singh. "Modelling default probabilities: The classical vs. machine learning approach." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273570.
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Fintech companies that offer Buy Now, Pay Later products are heavily dependent on accurate default probability models. This is since the fintech companies bear the risk of customers not fulfilling their obligations. In order to minimize the losses incurred to customers defaulting several machine learning algorithms can be applied but in an era in which machine learning is gaining popularity, there is a vast amount of algorithms to select from. This thesis aims to address this issue by applying three fundamentally different machine learning algorithms in order to find the best algorithm according to a selection of chosen metrics such as ROCAUC and precision-recall AUC. The algorithms that were compared are Logistic Regression, Random Forest and CatBoost. All these algorithms were benchmarked against Klarna's current XGBoost model. The results indicated that the CatBoost model is the optimal one according to the main metric of comparison, the ROCAUC-score. The CatBoost model outperformed the Logistic Regression model by seven percentage points, the Random Forest model by three percentage points and the XGBoost model by one percentage point.Fintechbolag som erbjuder Köp Nu, Betala Senare-tjänster är starkt beroende av välfungerande fallissemangmodeller. Detta då dessa fintechbolag bär risken av att kunder inte betalar tillbaka sina krediter. För att minimera förlusterna som uppkommer när en kund inte betalar tillbaka finns flera olika maskininlärningsalgoritmer att applicera, men i dagens explosiva utveckling på maskininlärningsfronten finns det ett stort antal algoritmer att välja mellan. Denna avhandling ämnar att testa tre olika maskininlärningsalgoritmer för att fastställa vilken av dessa som presterar bäst sett till olika prestationsmått så som ROCAUC och precision-recall AUC. Algoritmerna som jämförs är Logistisk Regression, Random Forest och CatBoost. Samtliga algoritmers prestanda jämförs även med Klarnas nuvarande XGBoost-modell. Resultaten visar på att CatBoost-modellen är den mest optimala sett till det primära prestationsmåttet ROCAUC. CatBoost-modellen var överlägset bättre med sju procentenheter högre ROCAUC än Logistisk Regression, tre procentenheter högre ROCAUC än Random Forest och en procentenhet högre ROCAUC än Klarnas nuvarande XGBoost-modell
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Dukes, Kais. "Statistical parsing by machine learning from a Classical Arabic treebank." Thesis, University of Leeds, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658551.
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Research into statistical parsing for English has enjoyed over a decade of successful results. However, adapting these models to other languages has met with difficulties. Previous comparative work has shown that Modern Arabic is one of the most difficult languages to parse due to rich morphology and free word order. Classical Arabic is the ancient form of Arabic, and is understudied in computational linguistics, relative to its worldwide reach as the language of the Quran. The thesis is based on seven publications that make significant contributions to knowledge relating to annotating and parsing Classical Arabic. Classical Arabic has been studied in depth by grammarians for over a thousand years using a traditional grammar known as i'rab. Using this grammar to develop a representation for parsing is challenging, as it describes syntax using a hybrid of phrase-structure and dependency relations. This work aims to advance the state-of-the-art for hybrid parsing by introducing a formal representation for annotation and a resource for machine learning. The main contributions are the first treebank for Classical Arabic and the first statistical dependency-based parser in any language for ellipsis, dropped pronouns and hybrid representations. A central argument of this thesis is that using a hybrid representation closely aligned to traditional grammar leads to improved parsing for Arabic. To test this hypothesis, two approaches are compared. As a reference, a pure dependency parser is adapted using graph transformations, resulting in an 87.47% F I-score. This is compared to an integrated parsing model with an F I-score of 89.03%, demonstrating that joint dependency-constituency parsing is better suited to Classical Arabic. The Quran was chosen for annotation as a large body of work exists providing detailed syntactic analysis. Volunteer crowdsourcing is used for annotation in combination with expert supervision. A practical result of the annotation effort is the corpus website: http://corpus.quran.com, an educational resource with over two million users per year.
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Pesah, Arthur. "Learning quantum state properties with quantum and classical neural networks." Thesis, KTH, Tillämpad fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252693.
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Soanes, Grant Paul. "Visual and chemical learning in the pond snail, Lymnaea stagnalis." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285369.
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Bertolucci, Franco. "Operant and classical learning in Drosophila melanogaster: the ignorant gene (ign)." kostenfrei, 2008. http://www.opus-bayern.de/uni-wuerzburg/volltexte/2009/3398/.
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Murphy, Robin A. J. "Relative contingency learning in Pavlovian conditioning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0026/NQ50226.pdf.
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Bodén, Johan. "A Comparative Study of Reinforcement-based and Semi-classical Learning in Sensor Fusion." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-84784.
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Reinforcement learning has proven itself very useful in certain areas, such as games. However, the approach has been seen as quite limited. Reinforcement-based learning has for instance not been commonly used for classification tasks as it is receiving feedback on how well it did for an action performed on a specific input. This slows the performance convergence rate as compared to other classification approaches which has the input and the corresponding output to train on. Nevertheless, this thesis aims to investigate whether reinforcement-based learning could successfully be employed on a classification task. Moreover, as sensor fusion is an expanding field which can for instance assist autonomous vehicles in understanding its surroundings, it is also interesting to see how sensor fusion, i.e., fusion between lidar and RGB images, could increase the performance in a classification task. In this thesis, a reinforcement-based learning approach is compared to a semi-classical approach. As an example of a reinforcement learning model, a deep Q-learning network was chosen, and a support vector machine classifier built on top of a deep neural network, was chosen as an example of a semi-classical model. In this work, these frameworks are compared with and without sensor fusion to see whether fusion improves their performance. Experiments show that the evaluated reinforcement-based learning approach underperforms in terms of metrics but mainly due to its slow learning process, in comparison to the semi-classical approach. However, on the other hand using reinforcement-based learning to carry out a classification task could still in some cases be advantageous, as it still performs fairly well in terms of the metrics presented in this work, e.g. F1-score, or for instance imbalanced datasets. As for the impact of sensor fusion, a notable improvement can be seen, e.g. when training the deep Q-learning model for 50 episodes, the F1-score increased with 0.1329; especially, when taking into account that the most of the lidar data used in the fusion is lost since this work projects the 3D lidar data onto the same 2D plane as the RGB images.
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Prato, D. E. "Developing unification in the teaching and learning of jazz and classical guitar." Thesis, University of Salford, 2017. http://usir.salford.ac.uk/43486/.
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I am a guitarist who dedicates to the styles of jazz and classical music. After starting out by playing folk and rock styles during my childhood, I later gravitated towards blues and funk and eventually jazz in my late teens, when I decided to become a full time musician. Later, in my mid twenties, I developed a passion for the classical guitar and eventually made the decision to dedicate 50% of my practice time to this style and 50% to jazz. Inevitably, as a result of a serious commitment to both styles, I have had a personal experience of what their study involves, how their value systems work and what aspects of music and guitar performance they each prioritize. I have found this experience deeply interesting because they both have developed a very advanced understanding of the instrument, but in very different areas. The first intention of this thesis is to identify what the differences are in the ideologies, teaching and learning of the guitar between the jazz and the classical genres. I then will contemplate whether a potential for an enhanced understanding of the instrument as a whole can be achieved in the future through the process of these styles each absorbing knowledge developed by the other. The research has been undertaken in the area of literature and instructional material for the instrument, as well as through interviews with guitarists in both fields. Additionally, I have included a chapter based on a reflective analysis of my own experience as a student of both genres. In order to facilitate the understanding of why these styles have developed in the way that they have, there is also a chapter dedicated to the historical context of the genres. Based on my findings, I have included a conclusion in the form of lessons aimed at guitarists in each style, presenting to them ways in which they can advance their understanding of the instrument based on knowledge developed within each other’s schools and ideologies. Finally, I have also created a DVD to support this proposal, with relevant demonstrations and performances on the instrument. These doctoral studies have conformed one of the most significant learning periods in my life as a musician and guitarist. I am fascinated by this subject and will continue to work on it through my ongoing research, playing and teaching. I hope that this work will help to generate more interest and research in this area of guitar playing.
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Torgerson, Richard C. Jr. "Relational Learning in the Analects of Confucius: Exploring the Foundations, Practices and Purposes of Classical Confucian Learning." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1500583837350483.
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Zhou, Sharon. "Engineering Ingenium: Improving Engagement and Accuracy With the Visualization of Latin for Language Learning." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14398527.
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The goal of Ingenium is to prompt beginning Latin students to think consciously and critically on Latin grammar prior to translating a sentence, while engaging them with the grammar in an intuitive and hands-on way. Learners commonly make errors in reading Latin, because they do not fully understand the impact of Latin’s grammatical structure—its morphology and syntax—on a sentence’s meaning. Synthesizing instructional methods used for Latin and artificial programming languages, Ingenium visualizes the logical structure of grammar by making each word into a puzzle block, whose shape and color reflect the word’s morphological forms and roles. Ingenium is designed so that students do not focus on words in isolation, but make logical connections between words and group words together, so that the number of elements involved in the translation, or the cognitive load, is instantly reduced. For this reason, puzzle blocks only fit together if there is sound grammatical logic, preventing students from making syntactic errors and allowing them to experiment in a mistake-free environment. The blocks also serve to abstract out the grammatical terminology in favor of visual representation, making it easy for Ingenium to supplement current methods of Latin instruction and to maximize its adoption potential.
The audience of Ingenium is novice Latin students. When students’ experience and confidence are at their lowest, they will benefit most from an interface that is not exclusively text-based, but engaging, hands-on, familiar, and intuitive. To evaluate Ingenium, I conducted an experiment with 67 beginning Latin students, measuring objective engagement, emotional and cognitive engagement, learning, change in self-efficacy, cognitive load, and accuracy in sentence translation with Ingenium over a traditional text-based interface as the baseline control. From the study, students, when using Ingenium, reported considerably higher levels of engagement and learning, opted to perform more optional problems, and completed translation exercises with substantially greater accuracy than when using the traditional interface. Ingenium has demonstrated its potential to be a powerful tool in improving students’ engagement, learning, and accuracy in reading Latin. Thus, Ingenium supports Latin pedagogy by introducing the following research-based innovations:
- An approach to learning a natural language through hands-on interactions with the logic of its grammar
- A method of visually and intuitively representing technical grammatical concepts
- A tool that can effectively engage early learners of Latin with the grammar of the language
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Murphy, Robin A. J. "Pavlovian conditioning is the consequence of more than just the number of CS-US pairings." Thesis, McGill University, 1993. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=69630.
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Three Pavlovian conditioning experiments with rats were performed to test predictions from models of associative learning. The procedure in all 3 experiments involved assessing conditioned responding to a Light that was compounded with either perfect or imperfect auditory signals for food. In Experiment 1 a partially reinforced Light which signaled 100% of the food pellets acquired a greater ability to elicit a conditioned response when the auditory cues with which it was paired were relatively poor predictors of the food. In Experiment 2 the Light was still a moderate positive predictor for food, but food was presented both in the presence and absence of the Light. Responding to the Light again was reliably higher when the auditory cues were poor predictors of food. Experiment 3 replicated the results from Experiment 2 and included two control conditions to assess sensitivity to the absolute validity of the Light. In both control conditions the Light was uncorrelated with the US. In one condition the number of food presentations was the same as in the experimental condition, while in the second the number of Light-food pairings was maintained. Results suggested that regardless of the absolute contingency of the Light responding was higher when the auditory cues were uncorrelated with food. These findings suggest that associative models of cue competition make accurate predictions of conditioned behavior following exposure to multiple predictors of reinforcement.
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Krasnyuk, Maxim, Antonina Tkalenko, and Svitlana Krasniuk. "Results of analysis of machine learning practice for training effective model of bankruptcy forecasting in emerging markets." Thesis, List Verlag. in Ullstein Buchverlage GmbH & Europäische Wissenschaftsplattform, 2021. https://er.knutd.edu.ua/handle/123456789/18975.
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All still existing classical techniques methods of assessing the financial stability of an enterprise have their own disadvantages and advantages. Therefore, today an important question arises about the development of such a complex multistage methodology of financial analysis and forecasting (hereinafter FAP), which would give a clear idea of the existing financial condition of the enterprise.
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Andrade, Valente da Silva Michelle. "SLAM and data fusion for autonomous vehicles : from classical approaches to deep learning methods." Thesis, Paris Sciences et Lettres (ComUE), 2019. http://www.theses.fr/2019PSLEM079.
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L'arrivée des voitures autonomes va provoquer une transformation très importante de la mobilité urbaine telle que nous la connaissons, avec un impact significatif sur notre vie quotidienne. En effet, elles proposent un nouveau système de déplacement plus efficace, plus facilement accessible et avec une meilleure sécurité routière. Pour atteindre cet objectif, les véhicules autonomes doivent effectuer en toute sécurité et de manière autonome trois tâches principales: la perception, la planification et le contrôle. La perception est une tâche particulièrement difficile en milieu urbain, car elle se doit d'être suffisamment précise pour assurer à la fois la sécurité du conducteur et celle des autres. Il est décisif d’avoir une bonne compréhension de l’environnement et de ses obstacles, ainsi qu’une localisation précise, afin que les autres tâches puissent être performantes. L'objectif de cette thèse est d'explorer différentes techniques pour la cartographie et la localisation des voitures autonomes en milieu urbain, en partant des approches classiques jusqu'aux algorithmes d'apprentissage profond. On s'intéresse plus spécifiquement aux véhicules équipés de capteurs bon marché avec l'idée de maintenir un prix raisonnable pour les futures voitures autonomes. Dans cette optique, nous utilisons dans les méthodes proposées des capteurs comme des scanner laser 2D, des caméras et des centrales inertielles à bas coût. Dans la première partie, nous introduisons des méthodes classiques utilisant des grilles d'occupation évidentielles. Dans un premier temps, nous présentons une nouvelle approche pour faire de la fusion entre une caméra et un scanner laser 2D pour améliorer la perception de l'environnement. De plus, nous avons ajouté une nouvelle couche dans notre grille d'occupation afin d'affecter un état à chaque objet détecté. Cet état permet de suivre l'objet et de déterminer s'il est statique ou dynamique. Ensuite, nous proposons une méthode de localisation s'appuyant sur cette nouvelle couche ainsi que sur des techniques de superposition d'images pour localiser le véhicule tout en créant une carte de l'environnement. Dans la seconde partie, nous nous intéressons aux algorithmes d'apprentissage profond appliqués à la localisation. D'abord, nous introduisons une méthode d'apprentissage pour l'estimation d'odométrie utilisant seulement des données issues de scanners laser 2D. Cette approche démontre l'intérêt des réseaux de neurones comme un bon moyen pour analyser ce type de données, dans l'optique d'estimer le déplacement du véhicule. Ensuite, nous étendons la méthode précédente en fusionnant le laser scanner 2D avec une caméra dans un système d'apprentissage de bout-en-bout. L'ajout de cette caméra permet d'améliorer la précision de l'estimation d'odométrie et prouve qu'il est possible de faire de la fusion de capteurs avec des réseaux de neurones. Finalement, nous présentons un nouvel algorithme hybride permettant à un véhicule de se localiser dans une région déjà cartographiée. Cet algorithme s'appuie à la fois sur une grille évidentielle prenant en compte les objets dynamiques et sur la capacité des réseaux de neurones à analyser des images. Les résultats obtenus lors de cette thèse nous ont permis de mieux comprendre les problématiques liées à l'utilisation de capteurs bon marché dans un environnement dynamique. En adaptant nos méthodes à ces capteurs et en introduisant une fusion de leur information, nous avons amélioré la perception générale de l'environnement ainsi que la localisation du véhicule. De plus, notre approche a permis d'identifier les avantages et inconvénients entre les différentes méthodes classiques et d'apprentissage. Ainsi, nous proposons une manière de combiner ces deux types d'approches dans un système hybride afin d'obtenir une localisation plus précise et plus robusteSelf-driving cars have the potential to provoke a mobility transformation that will impact our everyday lives. They offer a novel mobility system that could provide more road safety, efficiency and accessibility to the users. In order to reach this goal, the vehicles need to perform autonomously three main tasks: perception, planning and control. When it comes to urban environments, perception becomes a challenging task that needs to be reliable for the safety of the driver and the others. It is extremely important to have a good understanding of the environment and its obstacles, along with a precise localization, so that the other tasks are well performed. This thesis explores from classical approaches to Deep Learning techniques to perform mapping and localization for autonomous vehicles in urban environments. We focus on vehicles equipped with low-cost sensors with the goal to maintain a reasonable price for the future autonomous vehicles. Considering this, we use in the proposed methods sensors such as 2D laser scanners, cameras and standard IMUs. In the first part, we introduce model-based methods using evidential occupancy grid maps. First, we present an approach to perform sensor fusion between a stereo camera and a 2D laser scanner to improve the perception of the environment. Moreover, we add an extra layer to the grid maps to set states to the detected obstacles. This state allows to track an obstacle overtime and to determine if it is static or dynamic. Sequentially, we propose a localization system that uses this new layer along with classic image registration techniques to localize the vehicle while simultaneously creating the map of the environment. In the second part, we focus on the use of Deep Learning techniques for the localization problem. First, we introduce a learning-based algorithm to provide odometry estimation using only 2D laser scanner data. This method shows the potential of neural networks to analyse this type of data for the estimation of the vehicle's displacement. Sequentially, we extend the previous method by fusing the 2D laser scanner with a camera in an end-to-end learning system. The addition of camera images increases the accuracy of the odometry estimation and proves that we can perform sensor fusion without any sensor modelling using neural networks. Finally, we present a new hybrid algorithm to perform the localization of a vehicle inside a previous mapped region. This algorithm takes the advantages of the use of evidential maps in dynamic environments along with the ability of neural networks to process images. The results obtained in this thesis allowed us to better understand the challenges of vehicles equipped with low-cost sensors in dynamic environments. By adapting our methods for these sensors and performing the fusion of their information, we improved the general perception of the environment along with the localization of the vehicle. Moreover, our approaches allowed a possible comparison between the advantages and disadvantages of learning-based techniques compared to model-based ones. Finally, we proposed a form of combining these two types of approaches in a hybrid system that led to a more robust solution
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Arbo, Desiree. "The uses of classical learning in the Río de la Plata, c. 1750-1815." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/91085/.
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This thesis explores the uses of classical learning in colonial Rio de la Plata and early independent Paraguay (c.1767-1815). It examines different ways in which classical influences are discernible: in the works of the Jesuit José Manuel Peramás (Chapters 1 and 2), in colonial classrooms and library inventories (Chapter 3), and in the political discourse of Paraguayan independence (Chapter 4). As missionaries, educators and authors of Latin literature, the Jesuits exerted a powerful cultural force in the Rio de la Plata until their expulsion in 1767, yet their legacy in the intellectual life of colonial Paraguay has been neglected; Paraguayan historians dismiss the colonial period as a time of cultural stagnation, only revived by the importation of Enlightenment ideas from Europe and North America in the late eighteenth century. Yet these same scholars have not satisfactorily explained the ideology of the independence, given that the political rhetoric of the new republics was not always consistent with Enlightenment ideals. My thesis takes a revisionist point of view, arguing that the uses of classical knowledge reflected broader intellectual trends in the transition from the colonial to independent periods which help explain the initial construction of national identities in the Rio de la Plata.
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Peri, Deepthi. "Applying Natural Language Processing and Deep Learning Techniques for Raga Recognition in Indian Classical Music." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99967.
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In Indian Classical Music (ICM), the Raga is a musical piece's melodic framework. It encompasses the characteristics of a scale, a mode, and a tune, with none of them fully describing it, rendering the Raga a unique concept in ICM. The Raga provides musicians with a melodic fabric, within which all compositions and improvisations must take place. Identifying and categorizing the Raga is challenging due to its dynamism and complex structure as well as the polyphonic nature of ICM. Hence, Raga recognition—identify the constituent Raga in an audio file—has become an important problem in music informatics with several known prior approaches. Advancing the state of the art in Raga recognition paves the way to improving other Music Information Retrieval tasks in ICM, including transcribing notes automatically, recommending music, and organizing large databases.
This thesis presents a novel melodic pattern-based approach to recognizing Ragas by representing this task as a document classification problem, solved by applying a deep learning technique. A digital audio excerpt is hierarchically processed and split into subsequences and gamaka sequences to mimic a textual document structure, so our model can learn the resulting tonal and temporal sequence patterns using a Recurrent Neural Network. Although training and testing on these smaller sequences, we predict the Raga for the entire audio excerpt, with the accuracy of 90.3% for the Carnatic Music Dataset and 95.6% for the Hindustani Music Dataset, thus outperforming prior approaches in Raga recognition.Master of Science
In Indian Classical Music (ICM), the Raga is a musical piece's melodic framework. The Raga is a unique concept in ICM, not fully described by any of the fundamental concepts of Western classical music. The Raga provides musicians with a melodic fabric, within which all compositions and improvisations must take place. Raga recognition refers to identifying the constituent Raga in an audio file, a challenging and important problem with several known prior approaches and applications in Music Information Retrieval. This thesis presents a novel approach to recognizing Ragas by representing this task as a document classification problem, solved by applying a deep learning technique. A digital audio excerpt is processed into a textual document structure, from which the constituent Raga is learned. Based on the evaluation with third-party datasets, our recognition approach achieves high accuracy, thus outperforming prior approaches.
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Dolter, Elizabeth. "Learning with the classics: an instructional anthology for the elementary to late intermediate pianist." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6096.
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Chihabi, Kutibh. "Protein Kinase Mzeta (PKM-ζ) Regulates Kv1.2 Dependent Cerebellar Eyeblink Classical Conditioning." ScholarWorks @ UVM, 2017. http://scholarworks.uvm.edu/graddis/719.
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Learning and memory has been a topic that has captured the attention of the scientific and public communities since the dawn of scientific discovery. Without the faculty of memory, mammals cannot experience nor function in the world; among homosapiens specifically, language, relationships, and personal identity cannot be developed (Eysenck, 2012). After all, some philosophers such as John Locke argued we are nothing but a collection of past memories in which we have developed and improved upon (Nimbalkar, 2011).
Understanding the cellular mechanisms behind learning, and the subsequent formation of memory, has been a topic that has garnered scientific interest for many decades. One particular kinase that has been at the center of attention in the last decade is the serine/threonine kinase PKM-ζ, an N-terminal truncated form of PKC-ζ that renders it constitutively active (Hernandez et al., 2003). PKM-ζ has long been implicated in a cellular correlate of learning, long-term potentiation (LTP). Inhibition of PKM-ζ with Zeta-inhibitory peptide (ZIP) has been shown in many brain structures to disrupt maintenance of AMPA receptors, irreversibly disrupting numerous forms of learning and memory that have been maintained for weeks.
The voltage-gated potassium channel Kv1.2 is a critical modulator of neuronal physiology, including dendritic excitability, action potential propagation, and
neurotransmitter release. While expressed in various mammalian tissues, Kv1.2 is most prevalent in the cerebellum where it modulates both dendritic excitability of Purkinje cells (PCs) and basket cell (BC) inhibitory input to PCs. Because PCs are the main computational unit of the cerebellar cortex and provide its sole output (Napper et al., 1988; Harvey et al., 1991), regulation of synaptic Kv1.2 is predicted to have a major role in cerebellar function. Pharmacological inhibition of Kv1.2 in cerebellar PC dendrites increases excitability (Khavandgar et al., 2005), while its inhibition in BC axon terminals increases inhibition to PCs (Southan & Robertson, 1998). Interestingly, two prior studies have demonstrated that PKC-ζ, an atypical Protein Kinase C, is able to phosphorylate and bind cerebellar Kvβ2, a Kv1.2 auxiliary subunit. (Gong et al., 1999; Croci et al., 2003).
Delay eyeblink conditioning (EBC) is an established model for the assessment of cerebellar learning. Despite being highly expressed in the cerebellum, no studies have examined how regulation of cerebellar PKM-ζ may affect cerebellar-dependent learning and memory nor have they examined the possible effect PKM-ζ may have on Kv1.2. The goal of this dissertation was to determine whether PKM-ζ could modulate EBC in a Kv1.2 dependent manner. Through the use of microscopy techniques we have shown that PKM-ζ is highly expressed in the cerebellar cortex, primarily in the PC, and by the use of pharmacological manipulations, it was found that PKM-ζ has an important role in regulating the acquisition of EBC. Through the use of biotinylation, flow cytometry, and behavioral manipulations, it was determined that PKM-ζ regulates Kv1.2 during eyeblink conditioning. These studies provided the first evidence that PKM-ζ has a role for learning and memory in the cerebellum, and the first evidence of PKM-ζ regulating a voltage-gated ion channel rather than a ligand-gated ion channel such as AMPA receptors.
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Eschbach, Claire [Verfasser], and Bertram [Akademischer Betreuer] Gerber. "Classical and operant learning in the larvae of Drosophila melanogaster / Claire Eschbach. Betreuer: Bertram Gerber." Würzburg : Universitätsbibliothek der Universität Würzburg, 2012. http://d-nb.info/1023205785/34.
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Chai, Sin-Chee 1969. "The functions of amygdala and hippocampus in conditioned cue preference learning /." Thesis, McGill University, 2002. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=38470.
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The experiments in this thesis examined the roles of stimulus configuration on conditioned cue preference (CCP) learning by asking what information is processed and by which neural substrates. Results from Experiments 1 and 2 showed that lesions of the lateral nucleus of the amygdala (LNA) but not of fimbria-fornix (FF) impaired CCP learning when the cues paired with food during training were distinct from those not paired with food in either of two different apparatuses. In Experiments 3 and 4 LNA lesions increased the size of the CCP when the cues paired with food and no food were ambiguous in two different apparatuses. Learning the ambiguous cue CCP required at least one session of unreinforced pre-exposure to the cues and was eliminated by FF lesions. In the last series of experiments, a latent learning effect of unreinforced pre-exposure on ambiguous cue CCP learning on the radial maze was found in normal animals that received at least 3 sessions of unreinforced pre-exposure. FF lesions made before, but not after, pre-exposure eliminated the latent learning effect. Hippocampus lesions made either before or after pre-exposure eliminated the CCP learning. Taken together, the results are consistent with the hypothesis that distinct cue CCP learning is based on conditioned approach responses to cues paired with food, mediated by a neural system that includes the LNA. The results also suggest that ambiguous cue CCP learning takes place in two phases. First spatial learning occurs during unreinforced pre-exposure, a process that requires an intact FF. Subsequently, information about the location of the reinforcer is added to the spatial information during the reinforced training trials by a process of "reconsolidation". An intact hippocampus is required for this process. The implications of these results and interpretations for latent learning and latent inhibition are considered.
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Paredes, Daniel A. "The role of norepinephrine in learning : cerebellar motor learning in rats." [Tampa, Fla] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0001922.
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Özaslan, Tan Hakan. "Computational analysis of expressivity in classical guitar performances." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/128877.
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L’estudi de l’expressivitat musical és un camp molt actiu en la computació musical. El seu interès ve donat per diverses motivacions: entendre i modelitzar l’expressivitat musical; identificar els recursos expressius que caracteritzen un instrument, gènere musical o intèrpret; i construir sistemes de síntesi amb la capacitat de reproduir música expresivament. Per abordar aquest problema tan ampli, la literatura existent tendeix a focalitzarse en instruments o gèneres musicals concrets. En aquesta tesi, ens hem focalitzat en l’anàlisi de la expressivitat en la guitarra clàssica y el nostre objectiu serà modelitzar l’ús de recursos expressius en aquest instrument. Els fonaments de tots els mètodes utilitzats en aquesta tesi estan basats en tècniques de búsqueda y recuperació de la informació, aprenentatge automàtic y processament del senyal. Concretament, combinem diversos algorismes de l’estat de l’art per fer una proposta de caracterització de l’ús dels recursos expressius. La guitarra clàssica és un instrument que es caracteritza per la diversitat de les seves possibilitats tímbriques. Els guitarristes professionals són capaços de transmetre molts matisos durant la interpretació d’una peça musical. Aquesta característica específica de la guitarra clàssica fa que l’anàlisi d’aquest instrument sigui una tasca difícil. Dividim el nostre anàlisi en dues línies de treball principals. La primera línia proposa una eina capaç d’identificar automàticament recursos expressius en el context d’una gravació comercial. Construim un model amb l’objectiu d’analitzar i extreure automàticament els tres recursos expressius més utilitzats: legato, glissando i vibrato. La segona línia proposa un anàlisi integral de desviacions de tempo en la guitarra clàssica. De les variacions, potser les més importants siguin les variacions de tempo: són fonamentals per a la interpretació expressiva i un ingredient clau per conferir una qualitat humana a interpretacions basades en ordinador. No obstant, la naturalesa d’aquestes variacions és encara un problema d’investigació que no ha estat resolt, amb diverses teories que apunten a un fenòmen multi-dimensional. El nostre sistema utilitza tècniques d’extracció de característiques i aprenentatge automàtic. La precisió de la classificació mostra que les desviacions de tempo són predictors precisos de la peça musical corresponent. Para recapitular, aquesta tesi contribueix al camp de l’anàlisi expressiu proveint un model automàtic d’articulació expressiva i un sistema predictor de peces musicals que analitza les desviacions de tempo. Finalment, aquesta tesi analitza el comportament dels models proposats utilitzant gravacions comercials.The study of musical expressivity is an active field in sound and music computing. The research interest comes from different motivations: to understand or model musical expressivity; to identify the expressive resources that characterize an instrument, musical genre, or performer; or to build synthesis systems able to play expressively. To tackle this broad problem, researchers focus on specific instruments and/or musical styles. Hence, in this thesis we focused on the analysis of the expressivity in classical guitar and our aim is to model the use of expressive resources of the instrument. The foundations of all the methods used in this dissertation are based on techniques from the fields of information retrieval, machine learning, and signal processing. We combine several state of the art analysis algorithms in order to deal with modeling the use of the expressive resources. Classical guitar is an instrument characterized by the diversity of its timbral possibilities. Professional guitarists are able to convey a lot of nuances when playing a musical piece. This specific characteristic of classical guitar makes the expressive analysis is a challenging task. The research conducted focuses on two different issues related to musical expressivity. First, it proposes a tool able to automatically identify expressive resources such as legato, glissando, and vibrato, in commercial guitar recordings. Second, we conducted a comprehensive analysis of timing deviations in classical guitar. Timing variations are perhaps the most important ones: they are fundamental for expressive performance and a key ingredient for conferring a human-like quality to machine-based music renditions. However, the nature of such variations is still an open research question, with diverse theories that indicate a multi-dimensional phenomenon. Our system exploits feature extraction and machine learning techniques. Classification accuracies show that timing deviations are accurate predictors of the corresponding piece. To sum up, this dissertation contributes to the field of expressive analysis by providing, an automatic expressive articulation model and a musical piece prediction system by using timing deviations. Most importantly, it analyzes the behavior of proposed models by using commercial recordings.
El estudio de la expresividad musical es un campo muy activo en la computación musical. El interés en investigar ésta área tiene distintas motivaciones: entender y modelar la expresividad musical; identificar los recursos expresivos que caracterizan un instrumento, género musical, o intérprete; y construir sistemas de síntesis con la capacidad de reproducir música expresivamente. Para abordar este problema tan amplio, la literatura existente tiende a enfocarse en instrumentos o géneros musicales específicos. En esta tesis nos enfocaremos en el análisis de la expresividad en la guitarra clásica y nuestro objetivo será modelar el uso de recursos expresivos en este instrumento. Los fundamentos de todos los métodos usados en esta tesis están basados en técnicas de búsqueda y recuperación de la información, aprendizaje automático y procesamiento de señales. Combinamos varios algoritmos del estado del arte para lidiar con el modelado del uso de los recursos expresivos. La guitarra clásica es un instrumento que se caracteriza por la diversidad de sus posibilidades tímbricas. Los guitarristas profesionales son capaces de transmitir muchos matices durante la interpretación de una pieza musical. Esta característica específica de la guitarra clásica hace que el análisis de este instrumento sea una tarea difícil. Dividimos nuestro análisis en dos líneas de trabajo principales. La primera línea propone una herramienta capaz de identificar automáticamente recursos expresivos en el contexto de una grabación comercial. Construimos un modelo con el objetivo de analizar y extraer automáticamente los tres recursos expresivos más utilizados: legato, glissando y vibrato. La segunda línea propone un análisis integral de desviaciones de tiempo en la guitarra clásica. De las variaciones, quizás las más importantes sean las variaciones de tiempo: son fundamentales para la interpretación expresiva y un ingrediente clave para conferir una cualidad humana a interpretaciones basadas en ordenador. No obstante, la naturaleza de tales variaciones es aún un problema de investigación que no ha sido resuelto, con diversas teorías que apuntan a un fenómeno multi-dimensional. Nuestro sistema utiliza técnicas de extracción de características y aprendizaje de automático. La precisión de la clasificación muestra que las desviaciones de tiempo son predictores precisos de la pieza musical correspondiente. Para recapitular, esta tesis contribuye al campo del análisis expresivo proveyendo un modelo automático de articulación expresiva y un sistema predictor de piezas musicales que emplea desviaciones de tiempo. Finalmente, esta tesis analiza el comportamiento de los modelos propuestos utilizando grabaciones comerciales.
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Mauldin, Kristin Noel. "EXAMINATION OF THE NEURAL CORRELATES UNDERLYING MULTIPLE-EXEMPLAR CATEGORY LEARNING IN BILATERAL RABBIT EYEBLINK CLASSICAL CONDITIONING." Miami University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=miami1190854129.
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Furze, Timothy Andrew. "The application of classical conditioning to the machine learning of a commonsense knowledge of visual events." Thesis, University of Leeds, 2013. http://etheses.whiterose.ac.uk/4688/.
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In the field of artificial intelligence, possession of commonsense knowledge has long been considered to be a requirementto construct a machine that possesses artificial general intelligence. The conventional approach to providing this commonsense knowledge is to manually encode the required knowledge, a process that is both tedious and costly. After an analysis of classical conditioning, it was deemed that constructing a system based upon the stimulusstimulus interpretation of classical conditioning could allow for commonsense knowledge to be learned through a machine directly and passively observing its environment. Based upon these principles, a system was constructed that uses a stream of events, that have been observed within the environment, to learn rules regarding what event is likely to follow after the observation of another event. The system makes use of a feedback loop between three sub-systems: one that associates events that occur together, a second that accumulates evidence that a given association is significant and a third that recognises the significant associations. The recognition of past associations allows for both the creation of evidence for and against the existence of a particular association, and also allows for more complex associations to be created by treating instances of strongly associated event pairs to be themselves events. Testing the abilities of the system involved simulating the three different learning environments. The results found that measures of significance based on classical conditioning generally outperformed a probability-based measure. This thesis contributes a theory of how a stimulus-stimulus interpretation classical conditioning can be used to create commonsense knowledge and an observation that a significant sub-set of classical conditioning phenomena likely exist to aid in the elimination of noise. This thesis also represents a significant departure from existing reinforcement learning systems as the system presented in this thesis does not perform any form of action selection.
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Ang, Kathryn. "Teaching Western classical piano music effectively in West Malaysia." Diss., University of Pretoria, 2013. http://hdl.handle.net/2263/41371.
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The existing curriculum for piano lessons in West Malaysia is over-reliant on the syllabi of foreign examination boards resulting in a fragmentary curriculum which denies the student access to a wider range of musical experiences. The aim of the study was to identify and suggest solutions to problems by analysing the teaching approaches of piano teachers and to determine if there are elements which are lacking in the lessons. It also aimed to provide solutions by establishing a theoretical framework for effective piano teaching with optimal lesson plans. This study made use of mixed methods research design.
A cross-sectional survey was conducted and data collection was by self-structured questionnaires. In addition, interviews were conducted for the qualitative component of this study. Twenty-five piano teachers with between one to twenty years of teaching experience were randomly selected to participate in the survey. A further fifteen interviews were conducted with teachers who were selected from the participants of the survey by purposive sampling. Interpretative phenomenology analysis was used to analyse the interviews in an effort to gain a better understanding of the nature and quality of the piano teaching in West Malaysia.
The study finds that having piano examinations with regularity, usually on a yearly basis, has largely dominated the curriculum with examination requirements and has resulted in several elements being missing or absent in a typical lesson. Hence the situation is clearly not ideal as lessons are too examination oriented. Furthermore, students are generally not exposed to sufficient opportunities to display their skills and musical achievements. These findings suggest that Western classical piano music can be taught more effectively in West Malaysia if teachers re-think their approach to teaching in terms of planning for an optimal lesson. This would involve having both long-term and short–term goals in which a variety of strategies and important elements are incorporated seamlessly using the “simultaneous learning” approach advocated by Harris, Crozier and Ley.Dissertation (MMus)--University of Pretoria, 2013.
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Fendel, Victoria Beatrix Maria. "Coptic interference in the syntax of Greek letters from Egypt." Thesis, University of Oxford, 2018. http://ora.ox.ac.uk/objects/uuid:36c39b84-b7f1-4eb5-b4b2-7556bf165deb.
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Egypt in the early Byzantine period was a bilingual country where Greek and Egyptian (Coptic) were used alongside each other. Historical studies as well as linguistic studies of the phonology and lexicon of early Byzantine Greek in Egypt testify to this situation. In order to describe the linguistic traces the language-contact situation left behind in individuals' linguistic output, this thesis analyses the syntax of early Byzantine Greek texts from Egypt. The primary object of interest is bilingual interference in the syntax of verbs, adverbial phrases, discourse organising devices and formulaic sections. The thesis is based on a corpus of Greek and Coptic private letters on papyrus, all of which date from the fourth to mid-seventh centuries, originate from Egypt and belong to bilingual, Greek-Coptic, papyrus archives. The data is analysed with a particular focus on three interrelated questions: (1) What kinds of deviations from the standard pattern appear and to what extent can language-internal confusion account for them? (2) How are instances of language-internal confusion and bilingual interference distributed over the selected syntactic domains? (3) Do deviations from the standard accumulate in certain letters or archives belonging to the corpus and do they correlate with additional indicators of bilingualism such as code-switching or circumstantial information about writers? In addition to answering these questions, the thesis seeks to explain the observed distributions. The results obtained from this study suggest that bilingual interference is linked to the way writers assimilated structures. In fact, there is a marked difference between deviating syntactic structures in non-formulaic and formulaic contexts. The study further suggests that bilingual interference does not affect every domain of syntax to the same degree. The degree of complexity of the syntactic structure in question as well as the degree of divergence from the corresponding Coptic structure seem to play a role.
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Mostofi, Abteen. "On the neurophysiology of cerebellar motor learning : an electrophysiological analysis of classical eyeblink conditioning in the rabbit." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608421.
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Frederico, Gustavo Cesar de Souza. "Feature selection and evaluation for genre classification of symbolically encoded classical music with the aid of machine learning." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27244.
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This work defines useful features for the classification of symbolically encoded music into 14 classical genres namely chorale, symphony, etude, fugue, prelude, contrafactum, sonata, mazurka, motet, sonatina, waltze, concerto, Gregorian chant and scherzo. Features are based on Music Theory and grouped into seven categories: distances in the harmonic mobius strip, distances on the line of fifths, scale, rhythmic syncopation and meter, polyphony measurements, duration and instrumentation. Features are extracted and ranked combining 5 filter-based methods. Six Machine Learning algorithms are defined for classification: three Support Vector Machines, one Bayesian network, the C4.5 and random forests. Using nested cross-validation for training and testing and considering all the features, the Bayesian network classifier yields 84.10% empirical accuracy. The FEATUROMETRE process measures the usefulness of the feature subsets in an approach similar to wrapper methods, conveying relevant information to domain experts. Another experiment measures the usefulness and accuracy of features individually and by category using FEATUROMETRE. Grouping the music pieces by their period, the measured accuracy with the random forest classifier in the second experiment reaches 89.81%.
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Robertson, Leena. "Early literacy in parallel literacy classes : young bilingual children learning to read in English, Urdu and classical Arabic." Thesis, Goldsmiths College (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413719.
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SPENCER, ROBERT LEON. "TOLERANCE DEVELOPMENT TO THE EFFECTS OF ETHANOL: ROLE OF BEHAVIORAL THERMOREGULATORY RESPONSES (BODY TEMPERATURE, CLASSICAL CONDITIONING, OPERANT LEARNING)." Diss., The University of Arizona, 1986. http://hdl.handle.net/10150/183874.
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The mechanisms which account for the diminished responsiveness (tolerance) of an individual to a drug, as a result of prior exposure to that drug, are not yet fully understood. Recently, it has been suggested that drug tolerance is a learned adaptive response. This possibility was examined by studying the effect of ethanol on body temperature and behavioral thermoregulatory responses of Sprague-Dawley rats. Two major studies were conducted. The first study examined the initial dose-related effects of ethanol (1, 2, or 3 g/kg i.p.); the second study examined the effect of ethanol (2.5 g/kg i.p.) administered on 14 consecutive days. Rats were tested in a thermocline, a hollo plexiglass tube in which a linear temperature gradient (6-36°C) was established through local heating and cooling of opposite ends of the tube. The position of rats in the thermocline was detected by a series of infrared light emitting diodes and photocells. The body temperature of rats in the thermocline was transmitted by a temperature sensitive telemetry capsule surgically placed in the peritoneal cavity. Validation studies demonstrated that rats reliably responded to temperature cues within the thermocline. In the first experiment ethanol produced a dose-related decrease in body temperature. All rats following injection initially selected an ambient temperature cooler than baseline. Rats receiving control treatment or the high dose of ethanol eventually shifted to a warmer ambient temperature. Activity levels were depressed equally by all three doses of ethanol. In the second experiment tolerance developed to the hypothermic effect of ethanol. A diminished response to ethanol was evident by the second test day and was maximal by day 7. Ethanol treated rats selected a cooler ambient temperature than control rats throughout the 14 day period, and activity levels continued to be depressed by ethanol throughout the 14 days. On the fifteenth day all rats were given an injection of saline. Rats which had previously received daily ethanol injections exhibited a hyperthermic response to saline compared to control rats. These results suggest that ethanol altered the central control of thermoregulation by lowering and possibly broadening the thermoregulatory set point. There was evidence for a conditioned hyperthermic response, but not a learned behavioral response, which contributed to the tolerance development.
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Maxfield, Lynn Milo. "Application of principles from motor-learning theory to the studio voice lesson: effects of feedback frequency on retention of classical singing technique." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/1021.
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Over the past several decades, cognitive and behavioral scientists have been researching the most effective practices for training muscles to produce specific movements consistently and accurately. That research has led to relatively wide acceptance of several best practices for the training of motor skills. One such practice is the reduction in the frequency with which augmented (external) feedback is provided by the instructor/trainer during skill-acquisition. This theory of low-frequency feedback has been examined by research in a wide variety of fields ranging from exercise and sport to voice therapy and rehabilitation. Prior to the study reported here, however, this theory had not been applied the acquisition of vocal skills associated with classical singing techniques. The current research consisted of an alternating treatment single-subject study, which was conducted on a college campus over the course of a 15-week semester. 8 college voice students (3 male and 5 female) ranging in age from 18 to 25 participated in voice lessons provided by the researcher and aimed at improving the overall quality of the voices of the participants. Over the course of the15 weeks, the instructor alternated between providing a high-frequency feedback (HFF) instruction condition and a low-frequency feedback (LFF) instruction condition. At the beginning of each session, a vocal sample was recorded to test the retention of the skills trained in the previous lesson. Those recordings were evaluated by a panel of five college voice instructors who provided a numerical score (out of a possible 100 pts.) for each sample on the basis of tone quality, breath management, and intonation. The results of this study indicated that three of the eight subjects retained more vocal skill ability during the HFF phases of the study, while the remaining five subjects retained less vocal skill ability during the HFF phases of the study. It was also seen that the three subjects who responded favorably to the HFF instruction condition were also those whose scores were higher throughout the duration of the study. These findings would appear to indicate that an HFF instruction condition may be more beneficial to more experienced or more skilled singers, while an LFF instruction condition may be more beneficial to more novice singers. In the final chapter of this report, several modifications to this study are suggested along with suggestions for future research regarding the application of other principles from motor-learning theory to the acquisition of new vocal skills.
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Riddoch, Jane. "The effect of classical music on painting quality, attitude and behaviour for students with severe intellectual disabilities." Connect to thesis, 2006. http://portal.ecu.edu.au/adt-public/adt-ECU2006.0050.html.
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Amundson, Jeffrey C. "CS-US temporal relations in blocking." Diss., Online access via UMI:, 2006.
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Shields-Más, Chelsea. "The Irish Christian holy men : Druids reinvented? /." Connect to online version, 2008. http://ada.mtholyoke.edu/setr/websrc/pdfs/www/2008/292.pdf.
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Kseibat, Dawod. "Adaptive intelligent tutoring for teaching modern standard Arabic." Thesis, University of Bedfordshire, 2010. http://hdl.handle.net/10547/134371.
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The aim of this PhD thesis is to develop a framework for adaptive intelligent tutoring systems (ITS) in the domain of Modern Standard Arabic language. This framework will comprise of a new approach to using a fuzzy inference mechanism and generic rules in guiding the learning process. In addition, the framework will demonstrate another contribution in which the system can be adapted to be used in the teaching of different languages. A prototype system will be developed to demonstrate these features. This system is targeted at adult English-speaking casual learners with no pre-knowledge of the Arabic language. It will consist of two parts: an ITS for learners to use and a teachers‘ tool for configuring and customising the teaching rules and artificial intelligence components among other configuration operations. The system also provides a diverse teaching-strategies‘ environment based on multiple instructional strategies. This approach is based on general rules that provide means to a reconfigurable prediction. The ITS determines the learner‘s learning characteristics using multiple fuzzy inferences. It has a reconfigurable design that can be altered by the teacher at runtime via a teacher-interface. A framework for an independent domain (i.e. pluggable-domain) for foreign language tutoring systems is introduced in this research. This approach allows the system to adapt to the teaching of a different language with little changes required. Such a feature has the advantages of reducing the time and cost required for building intelligent language tutoring systems. To evaluate the proposed system, two experiments are conducted with two versions of the software: the ITS and a cut down version with no artificial intelligence components. The learners used the ITS had shown an increase in scores between the post-test and the pre-test with learning gain of 35% compared to 25% of the learners from the cut down version.
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Witnauer, James E. "Reduced blocking as a result of increasing the number of blocking cues." Diss., Online access via UMI:, 2007.
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Heimisson, Gudmundur Torfi. "The importance of program-delivered differential reinforcement in the development of classical music auditory discrimination." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000440.
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Vigran, Joshua. "The Rise and Fall of Piano Improvisation in Western Classical Music Performance: Why Today's Piano Students Should be Learning to Improvise." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1703338/.
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Improvisation is an art form which has arguably been present since the existence of music itself. Inventing music on the spot, like spontaneous speech, is a common expression of artistry throughout history and across musical boundaries. While improvisation has maintained its importance in jazz, classical organ music and the music of many eastern cultures, this dissertation will focus on the presence of improvisation as acceptable performance practice within the tradition of western classical music. At several points in history, this musical tradition was encouraged and even expected to be a regular part of a musician's life, and yet in the classical music tradition of the twenty-first century, improvisation is rarely, if ever, heard from the concert stage, nor is it regularly included in the general education of the conservatory student.
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DELAHAYE, QUENTIN. "Framework for Classical Conditioning in a MobileRobot: Development of Pavlovian Model andDevelopment of Reinforcement Learning Algorithmto Avoid and Predict Noxious Events." Thesis, Örebro universitet, Institutionen för naturvetenskap och teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-35771.
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Nowadays, robots have more and more sensors and the technologies allow using them with less contraints as before. Sensors are important to learn about the environment. But the sensors can be used for classical conditioning, and create behavior for the robot. One of the behavior developed in this thesis is avoiding and predicting obstacles. The goal of this thesis is to propose a model which consists of developing a specific behavior to avoid noxious event, obstacles.
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Zalkow, Frank [Verfasser], Meinard [Akademischer Betreuer] Müller, Meinard [Gutachter] Müller, and Sebastian [Gutachter] Stober. "Learning Audio Representations for Cross-Version Retrieval of Western Classical Music / Frank Zalkow ; Gutachter: Meinard Müller, Sebastian Stober ; Betreuer: Meinard Müller." Erlangen : Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), 2021. http://d-nb.info/1237107806/34.
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Wheeler, Daniel S. "Contrasting reduced overshadowing and forward blocking." Diss., Online access via UMI:, 2006.
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Lipinski, Ryan Edward. "Superattraction: The superlearning phenomenon in interpersonal attraction." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2809.
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This thesis will discuss Pavlovian conditioning and its utility in researching various areas of psychology including interpersonal attraction. It was designed to extend the application of conditioning principles in the study of interpersonal attraction by testing cue competition predictions made by the reinforcement-context theory of attraction.
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Masada, Kristen S. "Chord Recognition in Symbolic Music: A Segmental CRF Model, Segment-Level Features, and Comparative Evaluations on Classical and Popular Music." Ohio University Honors Tutorial College / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1524847168750137.
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Anjos, Kátia Silva Souza dos. "O corpo cênico do balé clássico: um estudo a partir de relatos de bailarinos (as) clássicos (as) brasileiros (as)." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/100/100135/tde-04022017-153411/.
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A presente pesquisa teve como objetivo compreender a naturalização do corpo cênico demandado pelo balé clássico. Buscamos investigar como se constrói a naturalização do corpo cênico, expressivo, no balé clássico, uma vez que o mesmo é pensado, pelos bailarinos pesquisados, como algo que é próprio do (a) bailarino (a); como um dom. A partir de uma abordagem metodológica qualitativa, utilizamos como técnicas de investigação a observação de espetáculos de balé e entrevistas semiestruturadas com bailarinos (as) clássicos (as) brasileiros (as), que apresentaram anos de atuação e que possuíam a técnica incorporada. As trajetórias profissionais foram distintas. Alguns desses bailarinos dançaram, por exemplo, balés de repertório completos, outros dançaram variações dessa modalidade. Alguns deles escolheram a profissão de professor (a) de balé, outros, são profissionais em companhias de dança no país, mas todos os entrevistados participaram de festivais de dança. Como resultado de pesquisa, destacam-se os seguintes aspectos: o corpo pleno de quem dança balé clássico; um corpo que já possui uma técnica explícita e implícita, incorporadas. Essas técnicas configuram uma aprendizagem, que se dá por meio da reprodução e imitação de trejeitos de bailarinos renomados, vistos como modelo e inspiração para os bailarinos entrevistados. São assim imitados aspectos que consideram adequados à cena. Ao mesmo tempo, os bailarinos buscam na própria vida, nas emoções do cotidiano, a inspiração e as sensações que possam ser externalizadas na cena. Para os indivíduos pesquisados, ser artista no balé clássico articula-se à ideia de dom por conta de um aprendizado inconsciente que se dá no cotidiano. Essa noção de dom no balé clássico não é recente, podendo ser vista desde o século XVII, articulada à ideia de liberdade e autonomia artística. Há assim, uma atualização dessa ideia, em outros termos, circunstâncias e percepçõesThis research aimed to understand the naturalization of the scenic body demanded by classical ballet. We seek to investigate how the naturalization of \"scenic body\", expressive, in classical ballet, since it is thought, researched by dancers, as something that is itself the dancer, as a gift. From a qualitative approach, we used as investigative techniques the observing ballet performances and semi-structured interviews with Brazilian classical dancers who had years of experience and that had the technique in their bodies. Professional trajectories were different. Some of these dancers, danced for example, repertory ballets and others danced variations of ballet. Some of them have chosen the ballet teaching profession others are professionals in dance companies in the country but all responders participated in dance festivals. As search result stand out the following: full body who dance classical ballet; a body that already has a \"explicit technique\" and \"implicit technique, in their bodies. These techniques constitute a learning that takes place through reproduction and imitation of renowned dancers renowned dancers seen as a model and inspiration for dancers interviewed. They are mimicked aspects that they consider adequate to the scene. At the same time the dancers seek in their lives, in everyday emotions, inspiration and feelings that can be placed in the scene. For individuals surveyed, being an artist in the classic ballet articulates the gift idea because of an unconscious learning that occurs in everyday life. This notion of gift in classical ballet is not new, it can be seen from the seventeenth century, linked to the idea of freedom and artistic autonomy. There is an update of that idea, in other terms, conditions and perceptions
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Stevanovic, Bettina. "The effect of learning on pitch and speech perception influencing perception of Shepard tones and McGurk syllables using classical and operant conditioning principles /." View thesis, 2007. http://handle.uws.edu.au:8081/1959.7/33694.
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Thesis (Ph.D.)--University of Western Sydney, 2007.A thesis submitted to the University of Western Sydney, College of Arts, School of Psychology in fulfilment of the requirements for the degree of Doctor of Philosophy. Includes bibliography.
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Esslin-Peard, M. S. "The art of practice : learning through the looking-glass : understanding the musical learning of popular and classical undergraduate musicians based upon their reflections about their experiences of a UK university performance course." Thesis, University of Liverpool, 2017. http://livrepository.liverpool.ac.uk/3008704/.
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Much has been written in the last 30 years about musical practice and performance, but there is little consensus over what practice really means, or how musicians progress by practising. Researchers tend to focus on specific elements in practice rather than taking a more holistic perspective. Whilst academics historically focused on (primarily Western) classical musicians, more recent research has focused upon popular, jazz and folk musicians, drawing on formal and informal learning models. This research project at the University of Liverpool focuses on the practice and performance experiences of both popular and classical undergraduate musicians as described in students’ reflective essays, acquired through informed consent. The method of assessment, combining 70% of marks for performance and 30% of marks for the reflective essay is, as far as can be ascertained, unique in comparable higher education institutions. The research questions address the roles of practice, performance and reflection in musical learning: • What experiences of practice and performance do the students describe in their reflective essays? • Do students develop an understanding of their practice and performance behaviours through their reflective essays? If so, how? • What role does reflection play in musical learning? Musical learning takes place not only through individual practice, but also in ensembles and bands, supported by feedback from tutors and peers and is firmly situated in the socio-cultural environment of the university and the city of Liverpool. Longitudinal findings suggest that classical and popular musicians start their performance studies with quite different musical experiences and expectations, dependent upon their prior learning. However, the process of writing an annual reflective essay seems to encourage students to think more critically about their practice and performance behaviours and they ask ‘How am I ... ’ or ‘How are we practising?’ which may lead to the adoption of a range of metacognitive practice strategies. The research findings point towards a validation of written reflection combined with performance as an appropriate method for assessing student musicians. Reflective practice acted as a unifying element between the popular and classical musicians. This study provides a contribution to knowledge for tertiary and secondary music educators, scholars and those involved in higher education course design.
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Hoffmann, Loren C. "Cerebellar theta oscillations are synchronized during hippocampal theta-contingent trace conditioning." Oxford, Ohio : Miami University, 2009. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=miami1251998588.
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Koelker, Rachel Lee. "Comparing a discriminative stimulus procedure to a pairing procedure: Conditioning neutral social stimuli to function as conditioned reinforcers." Thesis, University of North Texas, 2009. https://digital.library.unt.edu/ark:/67531/metadc12143/.
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Social stimuli that function as reinforcers for most children generally do not function as reinforcers for children diagnosed with autism. These important social stimuli include smiles, head nods, thumb-ups, and okay signs. It should be an important goal of therapy for children with autism to condition these neutral social stimuli to function as reinforcers for children diagnosed with autism. There is empirical evidence to support both a pairing procedure (classical conditioning) and a discriminative stimulus procedure to condition neutral stimuli to function as reinforcers. However, there is no clear evidence as to the superiority of effectiveness for either procedure. Despite this most textbooks and curriculum guides for children with autism state only the pairing procedure to condition neutral stimuli to function as reinforcers. Recent studies suggest that the discriminative stimulus procedure may in fact be more effective in conditioning neutral stimuli to function as reinforcers for children diagnosed with autism. The present research is a further comparison of these two procedures. Results from one participant support recent findings that suggest the discriminative stimulus procedure is more effective in conditioning neutral stimuli to function as reinforcers. But the results from the other participant show no effects from either procedure, suggesting future research into conditions necessary to condition neutral social stimuli to function as reinforcers for children with autism.
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Fathi, Kazerouni Masoud [Verfasser], and Klaus-Dieter [Gutachter] Kuhnert. "Fully-automated plant recognition systems in challenging controlled and uncontrolled environments using classical and Deep Learning methods / Masoud Fathi Kazerouni ; Gutachter: Klaus-Dieter Kuhnert." Siegen : Universitätsbibliothek der Universität Siegen, 2019. http://d-nb.info/1208506811/34.
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