Prosodic Morphology : Gender in Arabic Perfect Active and Passive 3rd Person Singular Verbs

Prosodic /template Morphology, that "draws heavily on the theoretical apparatus and formalisms of the generative phonology model known as autosegmental phonology" (Katamba, F. 1993: 154), is the best analysis that can handle Arabic morphology. Verbs in Arabic are represented on three independent tiers: root tier, the skeletal tier and the vocalic melody tier (Katamba, F. 1993). Vowel morphemes, which are represented by diacritics, are inserted within the consonant morphemes, which are represented by primary symbols, to form words. The morpheme tier hypothesis paves the way to understand the nonconcatenative Arabic morphology. This paper analyzes gender in perfect active and passive 3rd person singular verbs on the basis of PM. The focus of the analysis shall be drawn heavily on the most common Arabic verbs; triconsonantal verbs, with brief introduction of the less common verbs; quadriconsonantal perfect active and passive masculine and feminine 3rd person singular verbs. I shall, too, cast the light on some vowel changes that some verbs undergo when voice changes.

Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

Quelques réflexions sur les origines de l'argot français du XXe siècle

Le but de ce mémoire est d’étudier les origines étymologiques des mots argotiques qui ont commencé à être utilisés pendant le vingtième siècle. 100 mots ont été choisis et présentés selon leurs origines. Les mots ont été choisis dans le Dictionnaire de l’argot et du français populaire. Les langues d’origine les plus représentées parmi ces 100 mots ont été étudiées pour voir s’il y a une raison probable pour laquelle le français a emprunté des mots à ces langues. Nous avons classé la plupart des mots en champs lexicaux pour examiner s’il y a un certain type de mots qui sont empruntés et si les langues différentes contribuent à des champs lexicaux différents. L’étude a montré que le français a emprunté des mots argotiques aux beaucoup de langues différentes pendant le vingtième siècle. L’anglais et l’arabe ont contribué avec le plus grand nombre de mots. Pour ces deux langues et pour la plupart des autres langues de l’étude, nous discutons des raisons possibles pour lesquelles les mots ont été empruntés.