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The Development of Writing and Preliterate SocietiesTung, Cynthia January 2015 (has links)
Thesis advisor: Michael J. Connolly / This paper explores the question of script choice for a preliterate society deciding to write their language down for the first time through an exposition on types of writing systems and a brief history of a few writing systems throughout the world. Societies sometimes invented new scripts, sometimes adapted existing ones, and other times used a combination of both these techniques. Based on the covered scripts ranging from Mesopotamia to Asia to Europe to the Americas, I identify factors that influence the script decision including neighboring scripts, access to technology, and the circumstances of their introduction to writing. Much of the world uses the Roman alphabet and I present the argument that almost all preliterate societies beginning to write will choose to use a version of the Roman alphabet. However, the alphabet does not fit all languages equally well, and the paper closes out with an investigation into some of these inadequacies and how languages might resolve these issues. / Thesis (BA) — Boston College, 2015. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Slavic and Eastern Languages and Literatures.
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The activity metric for low resource, on-line character recognitionConfer, William James January 2005 (has links) (PDF)
Thesis (Ph.D.)--Auburn University, 2005. / Abstract. Vita. Includes bibliographic references (ℓ. 97-100)
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Shapester's magic alphabet exegesis [thesis] submission to Auckland University of Technology as partial fulfilment of the degree of Master of Art and Design, March 2003.Austin, Logan. January 2003 (has links) (PDF)
Thesis (MA--Art and Design) -- Auckland University of Technology, 2003. / On cover : 2004 Also held in print (37 leaves : col. ill. ; 30 cm. + CD-ROM) in Wellesley Theses Collection (T 709.93074 AUS)
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Learning regular languages over large alphabets / Apprentissage de langages réguliers sur des alphabets de grandes taillesMens, Irini-Eleftheria 10 October 2017 (has links)
L'apprentissage de langages réguliers est un sous-ensemble de l'apprentissage automatique qui s'est révélé utile dans de nombreux domaines tels que l'intelli-gence artificielle, les réseaux de neurones, l'exploration de données, la vérification, etc. De plus, l'intérêt dans les langages définis sur des alphabets infinis ou de grande taille est croissant au fil des années. Même si plusierurs propriétés et théories se généralisent à partir du cas fini, l'apprentissage de tels langages est une tâche difficile.En effet, dans ce contexte, l'application naïve des algorithmes d'apprentissage traditionnel n'est pas possible.Dans cette thèse, nous présentons un schéma algorithmique général pour l'ap-prentissage de langages définis sur des alphabets infinis ou de grande taille, comme par exemple des sous-ensembles bornés de N or R ou des vecteurs booléens de grandes dimensions. Nous nous restreignons aux classes de langages qui sont acceptés par des automates déterministes symboliques utilisant des prédicats pour définir les transitions, construisant ainsi une partition finie de l'alphabet pour chaque état.Notre algorithme d'apprentissage, qui est une adaptation du L* d'Angluin, combine l'apprentissage classique d'un automate par la caractérisation de ses états, avec l'apprentissage de prédicats statiques définissant les partitions de l'alphabet. Nous utilisons l'apprentissage incrémental avec la propriété que deux types de requêtes fournissent une information suffisante sur le langage cible. Les requêtes du premier type sont les requêtes d'adhésions, qui permettent de savoir si un mot proposé appartient ou non au langage cible. Les requêtes du second type sont les requêtes d'équivalence, qui vérifient si un automate proposé accepte le langage cible; dans le cas contraire, un contre-exemple est renvoyé.Nous étudions l'apprentissage de langages définis sur des alphabets infinis ou de grande tailles dans un cadre théorique et général, mais notre objectif est de proposer des solutions concrètes pour un certain nombre de cas particuliers. Ensuite, nous nous intéressons aux deux principaux aspects du problème. Dans un premier temps, nous supposerons que les requêtes d'équivalence renvoient toujours un contre-exemple minimal pour un ordre de longueur-lexicographique quand l'automate proposé est incorrect. Puis dans un second temps, nous relâchons cette hypothèse forte d'un oracle d'équivalence, et nous la remplaçons avec une hypothèse plus réaliste où l'équivalence est approchée par un test sur les requêtes qui utilisent un échantillonnage sur l'ensemble des mots. Dans ce dernier cas, ce type de requêtes ne garantit pas l'obtention de contre-exemples, et par conséquent de contre-exemples minimaux. Nous obtenons alors une notion plus faible d'apprent-issage PAC (Probably Approximately Correct), permettant l'apprentissage d'une approximation du langage cible.Tout les algorithmes ont été implémentés, et leurs performances, en terme de construction d'automate et de taille d'alphabet, ont été évaluées empiriquement. / Learning regular languages is a branch of machine learning, which has been proved useful in many areas, including artificial intelligence, neural networks, data mining, verification, etc. On the other hand, interest in languages defined over large and infinite alphabets has increased in recent years. Although many theories and properties generalize well from the finite case, learning such languages is not an easy task. As the existing methods for learning regular languages depends on the size of the alphabet, a straightforward generalization in this context is not possible.In this thesis, we present a generic algorithmic scheme that can be used for learning languages defined over large or infinite alphabets, such as bounded subsets of N or R or Boolean vectors of high dimensions. We restrict ourselves to the class of languages accepted by deterministic symbolic automata that use predicates to label transitions, forming a finite partition of the alphabet for every state.Our learning algorithm, an adaptation of Angluin's L*, combines standard automaton learning by state characterization, with the learning of the static predicates that define the alphabet partitions. We use the online learning scheme, where two types of queries provide the necessary information about the target language. The first type, membership queries, answer whether a given word belongs or not to the target. The second, equivalence queries, check whether a conjectured automaton accepts the target language, a counter-example is provided otherwise.We study language learning over large or infinite alphabets within a general framework but our aim is to provide solutions for particular concrete instances. For this, we focus on the two main aspects of the problem. Initially, we assume that equivalence queries always provide a counter-example which is minimal in the length-lexicographic order when the conjecture automaton is incorrect. Then, we drop this ``strong'' equivalence oracle and replace it by a more realistic assumption, where equivalence is approximated by testing queries, which use sampling on the set of words. Such queries are not guaranteed to find counter-examples and certainly not minimal ones. In this case, we obtain the weaker notion of PAC (probably approximately correct) learnability and learn an approximation of the target language. All proposed algorithms have been implemented and their performance, as a function of automaton and alphabet size, has been empirically evaluated.
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« Diverse escriture d’un mesme nom » : translittérer les écritures orientales en alphabet latin dans la France de l’humanisme / “Diverse escriture d’un mesme nom” : transliteration of Oriental Scripts into Latin Alphabet in the France of HumanismTorrens, Antoine 05 February 2018 (has links)
La translittération est la transcription, signe par signe, d’un système d’écriture vers un autre. Relevant à la fois de l’histoire, de la linguistique et de la science des écritures – ou grammatologie –, ce travail vise à dégager les enjeux de la notion récente de translittération, appliquée à une période où elle n’était pas encore formulée ainsi, la Renaissance française. Il délimite les domaines respectifs de la translittération, de la transcription, de la traduction et du saut de code. Cette thèse prend pour point de départ les découvertes récentes sur l’hébreu dans l’humanisme français et met à profit les avancées en archéologie et en sciences cognitives concernant l’histoire de l’alphabet latin et son appréhension par ses utilisateurs. Elle s’appuie sur un corpus d’alphabets, de grammaires et de bibles du XVIe siècle pour mettre en relation les dimensions diachronique et diatopique des systèmes d’écriture. Elle montre que la pratique de la conversion d’écriture s’appuie moins sur les caractéristiques de l’écriture d’origine que sur une extension considérable de l’écriture d’arrivée. / Transliteration is the transcription sign by sign from a writing system to another. Being a matter of history, linguistics and study of writing systems – or grammatology – this work aims at identifying the issues of the quite recent notion of transliteration, as applied to a period when it was not formulated in this way, the French Renaissance. It delineates the respective fields of transliteration, transcription, translation and code-switching. This thesis takes as a starting point the recent findings on Hebrew in the French humanism and makes use of the advances in archeology and in cognitive science regarding the history of the Latin alphabet and its understanding by its users. It relies on a corpus of alphabets, grammars and bibles of the 16th century to link the diachronic and diatopic dimensions of writing systems. It shows that conversion of scripts as a practice relies less on the specific features of the source script than on a considerable extension of the target script.
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State-independent decodable DC-free codes with complex-valued signalling alphabetsJamieson, Craig Unknown Date
No description available.
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Equivalence of Classical and Quantum CodesPllaha, Tefjol 01 January 2019 (has links)
In classical and quantum information theory there are different types of error-correcting codes being used. We study the equivalence of codes via a classification of their isometries. The isometries of various codes over Frobenius alphabets endowed with various weights typically have a rich and predictable structure. On the other hand, when the alphabet is not Frobenius the isometry group behaves unpredictably. We use character theory to develop a duality theory of partitions over Frobenius bimodules, which is then used to study the equivalence of codes. We also consider instances of codes over non-Frobenius alphabets and establish their isometry groups. Secondly, we focus on quantum stabilizer codes over local Frobenius rings. We estimate their minimum distance and conjecture that they do not underperform quantum stabilizer codes over fields. We introduce symplectic isometries. Isometry groups of binary quantum stabilizer codes are established and then applied to the LU-LC conjecture.
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Písma, obsahy a čas. Vizuální komunikace / Alphabets, contents and the time. Visual communicationTojnarová, Lenka January 2010 (has links)
The theme of the diploma dissertation became a view of a field of alphabets (letters and types) in contexts of communication, history, art and education. The theoretical part is focused on historical, contemporary movements of the phenomenon all at once. Inclusive of reflecting on alphabets in art and also links to a medial communication. The second part of the diploma dissertation reacts to the strongest and the most inspiring moments. It focuses on a practical applications for art lessons. The third part [artistic] takes advantage of media knowledges and art lessons. They are interfaced into an interactive teaching material which challenges students to an active perception of visual culture.
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Synthesis of Partial Behavior Models from Overlapping Scenarios with Alternative AlphabetsLAFI, MOHAMMED FAYEQ January 2011 (has links)
No description available.
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Template-basierte Klassifikation planarer GestenSchmidt, Michael 09 July 2014 (has links) (PDF)
Pervasion of mobile devices led to a growing interest in touch-based interactions. However, multi-touch input is still restricted to direct manipulations. In current applications, gestural commands - if used at all - are only exploiting single-touch. The underlying motive for the work at hand is the conviction that a realization of advanced interaction techniques requires handy tools for supporting their interpretation. Barriers for own implementations of procedures are dismantled by providing proof of concept regarding manifold interactions, therefore, making benefits calculable to developers. Within this thesis, a recognition routine for planar, symbolic gestures is developed that can be trained by specifications of templates and does not imply restrictions to the versatility of input. To provide a flexible tool, the interpretation of a gesture is independent of its natural variances, i.e., translation, scale, rotation, and speed. Additionally, the essential number of specified templates per class is required to be small and classifications are subject to real-time criteria common in the context of typical user interactions. The gesture recognizer is based on the integration of a nearest neighbor approach into a Bayesian classification method.
Gestures are split into meaningful, elementary tokens to retrieve a set of local features that are merged by a sensor fusion process to form a global maximum-likelihood representation. Flexibility and high accuracy of the approach is empirically proven in thorough tests. Retaining all requirements, the method is extended to support the prediction of partially entered gestures. Besides more efficient input, the possible specification of direct manipulation interactions by templates is beneficial. Suitability for practical use of all provided concepts is demonstrated on the basis of two applications developed for this purpose and providing versatile options of multi-finger input. In addition to a trainable recognizer for domain-independent sketches, a multi-touch text input system is created and tested with users. It is established that multi-touch input is utilized in sketching if it is available as an alternative. Furthermore, a constructed multi-touch gesture alphabet allows for more efficient text input in comparison to its single-touch pendant. The concepts presented in this work can be of equal benefit to UI designers, usability experts, and developers of feedforward-mechanisms for dynamic training methods of gestural interactions. Likewise, a decomposition of input into tokens and its interpretation by a maximum-likelihood matching with templates is transferable to other application areas as the offline recognition of symbols. / Obwohl berührungsbasierte Interaktionen mit dem Aufkommen mobiler Geräte zunehmend Verbreitung fanden, beschränken sich Multi-Touch Eingaben größtenteils auf direkte Manipulationen. Im Bereich gestischer Kommandos finden, wenn überhaupt, nur Single-Touch Symbole Anwendung. Der vorliegenden Arbeit liegt der Gedanke zugrunde, dass die Umsetzung von Interaktionstechniken mit der Verfügbarkeit einfach zu handhabender Werkzeuge für deren Interpretation zusammenhängt. Auch kann die Hürde, eigene Techniken zu implementieren, verringert werden, wenn vielfältige Interaktionen erprobt sind und ihr Nutzen für Anwendungsentwickler abschätzbar wird. In der verfassten Dissertation wird ein Erkenner für planare, symbolische Gesten entwickelt, der über die Angabe von Templates trainiert werden kann und keine Beschränkung der Vielfalt von Eingaben auf berührungsempfindlichen Oberflächen voraussetzt. Um eine möglichst flexible Einsetzbarkeit zu gewährleisten, soll die Interpretation einer Geste unabhängig von natürlichen Varianzen - ihrer Translation, Skalierung, Rotation und Geschwindigkeit - und unter wenig spezifizierten Templates pro Klasse möglich sein. Weiterhin sind für Nutzerinteraktionen im Anwendungskontext übliche Echtzeit-Kriterien einzuhalten. Der vorgestellte Gestenerkenner basiert auf der Integration eines Nächste-Nachbar-Verfahrens in einen Ansatz der Bayes\'schen Klassifikation.
Gesten werden in elementare, bedeutungstragende Einheiten zerlegt, aus deren lokalen Merkmalen mittels eines Sensor-Fusion Prozesses eine Maximum-Likelihood-Repräsentation abgeleitet wird. Die Flexibilität und hohe Genauigkeit des statistischen Verfahrens wird in ausführlichen Tests nachgewiesen. Unter gleichbleibenden Anforderungen wird eine Erweiterung vorgestellt, die eine Prädiktion von Gesten bei partiellen Eingaben ermöglicht. Deren Nutzen liegt - neben effizienteren Eingaben - in der nachgewiesenen Möglichkeit, per Templates spezifizierte direkte Manipulationen zu interpretieren. Zur Demonstration der Praxistauglichkeit der präsentierten Konzepte werden exemplarisch zwei Anwendungen entwickelt und mit Nutzern getestet, die eine vielseitige Verwendung von Mehr-Finger-Eingaben vorsehen. Neben einem Erkenner trainierbarer, domänenunabhängiger Skizzen wird ein System für die Texteingabe mit den Fingern bereitgestellt. Anhand von Nutzerstudien wird gezeigt, dass Multi-Touch beim Skizzieren verwendet wird, wenn es als Alternative zur Verfügung steht und die Verwendung eines Multi-Touch Gestenalphabetes im Vergleich zur Texteingabe per Single-Touch effizienteres Schreiben zulässt. Von den vorgestellten Konzepten können UI-Designer, Usability-Experten und Entwickler von Feedforward-Mechanismen zum dynamischen Lehren gestischer Eingaben gleichermaßen profitieren. Die Zerlegung einer Eingabe in Token und ihre Interpretation anhand der Zuordnung zu spezifizierten Templates lässt sich weiterhin auf benachbarte Gebiete, etwa die Offline-Erkennung von Symbolen, übertragen.
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