OODINI 2.1 : an enhanced graphical schema representation for object-oriented database

The graphical representation of an object-oriented database (OODB) schema is useful for the designers and users of a database system. The purpose of my thesis was to enhance the existing version of OOdini, an interactive graphical tool for editing an OODB schema. The new features include interactive modification and description of objects in the schema. Data structures for representing classes and attributes have been altered to incorporate object/data types as well as a descriptive string. The software has been implemented using the ObjectMaker toolkit to design our own methodology using the ObjectMaker Extension Language

English lexical and semantic loans in informal spoken Polish

Celem niniejszej monografii jest opisanie najnowszych anglicyzmów leksykalnych i semantycznych występujących we współczesnej potocznej polszczyźnie mówionej. Podstawą badań jest korpus złożony z 20 rozmów codziennych, nagranych, przetranskrybowanych i przeanalizowanych przez autora pracy. Korpus składa się z ponad 60 000 słów. Autor zdecydował się na badanie zapożyczeń w języku mówionym, jako że wyrazy obce w języku pisanym (zwłaszcza prasowym) zostały dość dobrze opisane, niewiele jest natomiast prac poświęconym zapożyczeniom — zwłaszcza semantycznym — w języku mówionym. Opisano zarówno poszczególne zapożyczenia (ich znaczenie, wymowę, kolokacje oraz kontekst, w jakim pojawiły się w korpusie), jak i scharakteryzowano je jako zjawisko globalne, czyli dokonano podziału zapożyczeń według rozmaitych kryteriów, na przykład według części mowy, częstotliwości ich występowania w korpusie czy też okresu, w którym trafiły do polszczyzny. Autor podjął również próbę ustalenia, w jakim stopniu pojawianie się zapożyczeń w języku mówionym jest zależne od tematu rozmowy i idiolektu rozmówców. Badania zilustrowano licznymi tabelami statystycznymi obrazującymi różne aspekty ilościowe i jakościowe znalezionych w korpusie zapożyczeń leksykalnych i semantycznych. W monografii opisano również różnorakie problemy metodologiczne, jakie stwarzało badanie zapożyczeń w języku mówionym. Autor zaproponował ponadto własną hipotezę na temat sposobów wprowadzania i rozprzestrzeniania się zapożyczeń semantycznych w polszczyźnie. Hipoteza ta związana jest z koncepcją „odpowiedników prymarnych”, stosowaną dotychczas w badaniach nad przyswajaniem i uczeniem się języków obcych. Wiele z opisanych w niniejszej pracy zapożyczeń leksykalnych i semantycznych nie zostało dotychczas opisanych w literaturze przedmiotu ani zarejestrowanych w słownikach języka polskiego czy wyrazów obcych. Takim zapożyczeniom poświęcono szczególną uwagę. Jednym z wniosków zawartych w pracy jest stwierdzenie, że o ile liczba zapożyczeń leksykalnych w języku mówionym w ostatnich latach nie wzrasta (co przeczy odczuciu większości Polaków), o tyle znacząco wzrosła liczba typów zapożyczeń semantycznych

Syntactic structure and modal interpretation: the case of basque "behar"

391 p.This dissertation is an investigation of the syntactic structure and modal interpretation of clauses involving the denominal necessity predicate behar `need¿ and an infinitival complement. On the one hand, it analyses the syntactic status of non-finite complements of denominal behar by examining their interaction with syntactic phenomena sensitive to different structural and locality conditions, and concludes that the infinitival complements of behar can correspond to different underlying structures. The largest type of infinitive is a non-restructuring infinitive that projects a full clausal architecture (i.e. a CP), and the smallest one is a reduced restructuring infinitive that projects up to vP. There is evidence for intermediate types projecting up to the inflectional domain (IP/TP). On the other hand, the dissertation examines the thematic and scope properties of the subjects in each of the different structural types and the modal interpretation that they can give rise to. On the basis of this analysis it is argued that modal interpretation is not constrained by any single factor (the presence of restructuring, the referential status of the subject and its relative scope vis-à-vis the modal predicate, among other frequently mentioned ones), but depends on the cumulative effect of several factors working together. The dissertation also shows the necessity of adopting a more fine-grained view of root modality, one that allows a simpler mapping of syntactic structures into modal meanings

Graph Theory and Universal Grammar

Tese arquivada ao abrigo da Portaria nº 227/2017 de 25 de Julho-Registo de Grau EstrangeiroIn the last few years, Noam Chomsky (1994; 1995; 2000; 2001) has gone quite far in the direction of simplifying syntax, including eliminating X-bar theory and the levels of D-structure and S-structure entirely, as well as reducing movement rules to a combination of the more primitive operations of Copy and Merge. What remain in the Minimalist Program are the operations Merge and Agree and the levels of LF (Logical Form) and PF (Phonological form). My doctoral thesis attempts to offer an economical theory of syntactic structure from a graph-theoretic point of view (cf. Diestel, 2005), with special emphases on the elimination of category and projection labels and the Inclusiveness Condition (Chomsky 1994). The major influences for the development of such a theory have been Chris Collins’ (2002) seminal paper “Eliminating labels”, John Bowers (2001) unpublished manuscript “Syntactic Relations” and the Cartographic Paradigm (see Belletti, Cinque and Rizzi’s volumes on OUP for a starting point regarding this paradigm). A syntactic structure will be regarded here as a graph consisting of the set of lexical items, the set of relations among them and nothing more

Efficient machine learning: models and accelerations

One of the key enablers of the recent unprecedented success of machine learning is the adoption of very large models. Modern machine learning models typically consist of multiple cascaded layers such as deep neural networks, and at least millions to hundreds of millions of parameters (i.e., weights) for the entire model. The larger-scale model tend to enable the extraction of more complex high-level features, and therefore, lead to a significant improvement of the overall accuracy. On the other side, the layered deep structure and large model sizes also demand to increase computational capability and memory requirements. In order to achieve higher scalability, performance, and energy efficiency for deep learning systems, two orthogonal research and development trends have attracted enormous interests. The first trend is the acceleration while the second is the model compression. The underlying goal of these two trends is the high quality of the models to provides accurate predictions. In this thesis, we address these two problems and utilize different computing paradigms to solve real-life deep learning problems. To explore in these two domains, this thesis first presents the cogent confabulation network for sentence completion problem. We use Chinese language as a case study to describe our exploration of the cogent confabulation based text recognition models. The exploration and optimization of the cogent confabulation based models have been conducted through various comparisons. The optimized network offered a better accuracy performance for the sentence completion. To accelerate the sentence completion problem in a multi-processing system, we propose a parallel framework for the confabulation recall algorithm. The parallel implementation reduce runtime, improve the recall accuracy by breaking the fixed evaluation order and introducing more generalization, and maintain a balanced progress in status update among all neurons. A lexicon scheduling algorithm is presented to further improve the model performance. As deep neural networks have been proven effective to solve many real-life applications, and they are deployed on low-power devices, we then investigated the acceleration for the neural network inference using a hardware-friendly computing paradigm, stochastic computing. It is an approximate computing paradigm which requires small hardware footprint and achieves high energy efficiency. Applying this stochastic computing to deep convolutional neural networks, we design the functional hardware blocks and optimize them jointly to minimize the accuracy loss due to the approximation. The synthesis results show that the proposed design achieves the remarkable low hardware cost and power/energy consumption. Modern neural networks usually imply a huge amount of parameters which cannot be fit into embedded devices. Compression of the deep learning models together with acceleration attracts our attention. We introduce the structured matrices based neural network to address this problem. Circulant matrix is one of the structured matrices, where a matrix can be represented using a single vector, so that the matrix is compressed. We further investigate a more flexible structure based on circulant matrix, called block-circulant matrix. It partitions a matrix into several smaller blocks and makes each submatrix is circulant. The compression ratio is controllable. With the help of Fourier Transform based equivalent computation, the inference of the deep neural network can be accelerated energy efficiently on the FPGAs. We also offer the optimization for the training algorithm for block circulant matrices based neural networks to obtain a high accuracy after compression

Perception of old towns, historicism, and temporality

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1986.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH.Includes bibliographical references (leaves 155-162).The crux of this inquiry deals with one of the qualities which have been attributed by architectural and urban design theorists to the old, traditional town - its overwhelming sense of visual unity. In this study, it is argued that this unity is somewhat of a perceptual aberration which might arise out of structuring the perceptions of the old town in terms of its common denominator of oldness. The all-pervading sense of age could, to a certain extent erase other irregularities, so that the old town may be cognized with a powerful sense of unity. The first part of the study plants this central issue within the larger context of architectural theories and practice. Certain aspects of the theories of Christopher Alexander and Aldo van Eyck which are contingent upon the issue of the old town are expounded. The issue is also linked with the widespread architectural movement in the eastern world to create a culturally and socially responsive architecture. An important corollary of this movement is the imagery of the old town. The second part of the study deals with a perceptual test conducted to gain some insight into how old buildings are perceived. Rome has been taken as a case for this inquiry. Finally, in the third part, attempts are made to explain the results of the test through phenomenological means. Certain notions of temporality which impinge upon the perception of the old town are briefly touched upon. The social and cultural intentions with which architects seek inspiration in such towns are also touched upon to gain a greater understanding of the central issue.by Ranabir Sengupta.M.S

A survey on adaptive random testing

Random testing (RT) is a well-studied testing method that has been widely applied to the testing of many applications, including embedded software systems, SQL database systems, and Android applications. Adaptive random testing (ART) aims to enhance RT's failure-detection ability by more evenly spreading the test cases over the input domain. Since its introduction in 2001, there have been many contributions to the development of ART, including various approaches, implementations, assessment and evaluation methods, and applications. This paper provides a comprehensive survey on ART, classifying techniques, summarizing application areas, and analyzing experimental evaluations. This paper also addresses some misconceptions about ART, and identifies open research challenges to be further investigated in the future work