The Object Agreement Restriction

[EN]This paper deals with the so-called Person Case Constraint (Bonet, 1991), a universal constraint blocking accusative clitics and object agreement morphemes other than third person when a dative is inserted in the same clitic/agreement cluster. The aim of this paper is twofold. First, we argue that the scope of the PCC is considerably broader than assumed in previous work, and that neither its formulation in terms of person (1st/2nd vs. 3rd)-case (accusative vs. dative) restrictions nor its morphological nature are part of the right descriptive generalization.We present evidence (i) that the PCC is triggered by the presence of an animacy feature in the object’s agreement set; (ii) that it is not case dependent, also showing up in languages that lack dative case; and (iii) that it is not morphologically bound. Second, we argue that the PCC, even if it is modified accordingly, still puts together two different properties of the agreement system that should be set apart: (i) a cross linguistic sensitivity of object agreement to animacy and (ii) a similarly widespread restriction on multiple object agreement observed crosslinguistically. These properties lead us to propose a new generalization, the Object Agreement Constraint (OAC): if the verbal complex encodes object agreement, no other argument can be licensed through verbal agreement.

Objektu-komunztadura XIX eta XX. mendeetako euskal gramatiketan

Beatriz Fernández eta Pablo Albizu (arg.)

XIX. mendeko euskal gramatikagintzari buruzko ikerketak

lx, 407 or. [Bibliografia: 345-397; Index nominum: 399-405; Taulen aurkibidea: 407]

Euskal Gramatika prozesatzen: Hastapenetako zenbait emaitza

Beñat Oihartzabali Gorazarre: Festschrift for Bernard Oyharçabal / Ricardo Etxepare, Ricardo Gómez, Joseba Andoni Lakarra (arg./eds)

The Effect of Indexing on the Complexity of Object Recognition

Many current recognition systems use constrained search to locate objects in cluttered environments. Previous formal analysis has shown that the expected amount of search is quadratic in the number of model and data features, if all the data is known to come from a sinlge object, but is exponential when spurious data is included. If one can group the data into subsets likely to have come from a single object, then terminating the search once a "good enough" interpretation is found reduces the expected search to cubic. Without successful grouping, terminated search is still exponential. These results apply to finding instances of a known object in the data. In this paper, we turn to the problem of selecting models from a library, and examine the combinatorics of determining that a candidate object is not present in the data. We show that the expected search is again exponential, implying that naﶥ approaches to indexing are likely to carry an expensive overhead, since an exponential amount of work is needed to week out each of the incorrect models. The analytic results are shown to be in agreement with empirical data for cluttered object recognition.

Learning object segmentation from video data

This memo describes the initial results of a project to create a self-supervised algorithm for learning object segmentation from video data. Developmental psychology and computational experience have demonstrated that the motion segmentation of objects is a simpler, more primitive process than the detection of object boundaries by static image cues. Therefore, motion information provides a plausible supervision signal for learning the static boundary detection task and for evaluating performance on a test set. A video camera and previously developed background subtraction algorithms can automatically produce a large database of motion-segmented images for minimal cost. The purpose of this work is to use the information in such a database to learn how to detect the object boundaries in novel images using static information, such as color, texture, and shape. This work was funded in part by the Office of Naval Research contract #N00014-00-1-0298, in part by the Singapore-MIT Alliance agreement of 11/6/98, and in part by a National Science Foundation Graduate Student Fellowship.

Two-dimensional Monte Carlo simulations of H i line formation in massive young stellar object disc winds

Massive young stellar objects (YSOs) are powerful infrared Hi line emitters. It has been suggested that these lines form in an outflow from a disc surrounding the YSO. Here, new two-dimensional Monte Carlo radiative transfer calculations are described which test this hypothesis. Infrared spectra are synthesized for a YSO disc wind model based on earlier hydrodynamical calculations. The model spectra are in qualitative agreement with the observed spectra from massive YSOs, and therefore provide support for a disc wind explanation for the Hi lines. However, there are some significant differences: the models tend to overpredict the Bra/Br? ratio of equivalent widths and produce line profiles which are slightly too broad and, in contrast to typical observations, are double-peaked. The interpretation of these differences within the context of the disc wind picture and suggestions for their resolution via modifications to the assumed disc and outflow structure are discussed. © 2005 RAS.

Stimulus Simplification and Object Representation: A Modeling Study

Tsunoda et al. (2001) recently studied the nature of object representation in monkey inferotemporal cortex using a combination of optical imaging and extracellular recordings. In particular, they examined IT neuron responses to complex natural objects and "simplified" versions thereof. In that study, in 42% of the cases, optical imaging revealed a decrease in the number of activation patches in IT as stimuli were "simplified". However, in 58% of the cases, "simplification" of the stimuli actually led to the appearance of additional activation patches in IT. Based on these results, the authors propose a scheme in which an object is represented by combinations of active and inactive columns coding for individual features. We examine the patterns of activation caused by the same stimuli as used by Tsunoda et al. in our model of object recognition in cortex (Riesenhuber 99). We find that object-tuned units can show a pattern of appearance and disappearance of features identical to the experiment. Thus, the data of Tsunoda et al. appear to be in quantitative agreement with a simple object-based representation in which an object's identity is coded by its similarities to reference objects. Moreover, the agreement of simulations and experiment suggests that the simplification procedure used by Tsunoda (2001) is not necessarily an accurate method to determine neuronal tuning.

Name agreement in picture naming: An ERP study

Name agreement is the extent to which different people agree on a name for a particular picture. Previous studies have found that it takes longer to name low name agreement pictures than high name agreement pictures. To examine the effect of name agreement in the online process of picture naming, we compared event-related potentials (ERPs) recorded whilst 19 healthy, native English speakers silently named pictures which had either high or low name agreement. A series of ERP components was examined: P1 approximately 120ms from picture onset, N1 around 170ms, P2 around 220ms, N2 around 290ms, and P3 around 400ms. Additionally, a late time window from 800 to 900ms was considered. Name agreement had an early effect, starting at P1 and possibly resulting from uncertainty of picture identity, and continuing into N2, possibly resulting from alternative names for pictures. These results support the idea that name agreement affects two consecutive processes: first, object recognition, and second, lexical selection and/or phonological encoding.

Fleshing Out and Losing Flesh: The Decomposing Corpse as Narrative Object in American Hardboiled Detective Fiction

This dissertation examines the corpse as an object in and of American hardboiled detective fiction written between 1920 and 1950. I deploy several theoretical frames, including narratology, body-as-text theory, object relations theory, and genre theory, in order to demonstrate the significance of objects, symbols, and things primarily in the clever and crafty work of Dashiell Hammett (1894-1961) and Raymond Chandler (1888-1959), but also touching on the writings of their lesser known accomplices. I construct a literary genealogy of American hardboiled detective fiction originating in the writings of Edgar Allan Poe, compare the contributions of classic or Golden Age detective fiction in England, and describe the socio-economic contexts, particularly the predominance of the “pulps,” that gave birth to the realism of the Hardboiled School. Taking seriously Chandler’s obsession with the art of murder, I engage with how authors pre-empt their readers’ knowledge of the tricks of the trade and manipulate their expectations, as well as discuss the characteristics and effect of the inimitable hardboiled style, its sharpshooting language and deadpan humour. Critical scholarship has rarely addressed the body and figure of the corpse, preferring to focus instead on the machinations of the femme fatale, the performance of masculinity, or the prevalence of violence. I cast new light on the world of hardboiled detective fiction by dissecting the corpse as the object that both motivates and de-composes (or rots away from) the narrative that makes it signify. I treat the corpse as an inanimate object, indifferent to representation, that destabilizes the integrity and self-possession, as well as the ratiocination, of the detective who authors the narrative of how the corpse came to be. The corpse is all deceptive and dangerous surface rather than the container of hidden depths of life and meaning that the detective hopes to uncover and reconstruct. I conclude with a chapter that is both critical denouement and creative writing experiment to reveal the self-reflexive (and at times metafictional) dimensions of hardboiled fiction. My dissertation, too, in the manner of hardboiled fiction, hopes to incriminate my readers as much as enlighten them.

The spatial distribution and temporal dynamics of brain regions activated during the perception of object and non-object patterns

Both animal and human studies suggest that the efficiency with which we are able to grasp objects is attributable to a repertoire of motor signals derived directly from vision. This is in general agreement with the long-held belief that the automatic generation of motor signals by the perception of objects is based on the actions they afford. In this study, we used magnetoencephalography (MEG) to determine the spatial distribution and temporal dynamics of brain regions activated during passive viewing of object and non-object targets that varied in the extent to which they afforded a grasping action. Synthetic Aperture Magnetometry (SAM) was used to localize task-related oscillatory power changes within specific frequency bands, and the time course of activity within given regions-of-interest was determined by calculating time-frequency plots using a Morlet wavelet transform. Both single subject and group-averaged data on the spatial distribution of brain activity are presented. We show that: (i) significant reductions in 10-25 Hz activity within extrastriate cortex, occipito-temporal cortex, sensori-motor cortex and cerebellum were evident with passive viewing of both objects and non-objects; and (ii) reductions in oscillatory activity within the posterior part of the superior parietal cortex (area Ba7) were only evident with the perception of objects. Assuming that focal reductions in low-frequency oscillations (< 30 Hz) reflect areas of heightened neural activity, we conclude that: (i) activity within a network of brain areas, including the sensori-motor cortex, is not critically dependent on stimulus type and may reflect general changes in visual attention; and (ii) the posterior part of the superior parietal cortex, area Ba7, is activated preferentially by objects and may play a role in computations related to grasping. © 2006 Elsevier Inc. All rights reserved.

Provocative feature deletion: a syntactic model of agreement alternations in noun incorporation contexts

The relationship between noun incorporation (NI) and the agreement alternations that occur in such contexts (NI Transitivity Alternations) remains inadequately understood. Three interpretations of these alternations (Baker, Aranovich & Golluscio 2005; Mithun 1984; Rosen 1989) are shown to be undermined by foundational or mechanical issues. I propose a syntactic model, adopting Branigan's (2011) interpretation of NI as the result of “provocative” feature valuation, which triggers generation of a copy of the object that subsequently merges inside the verb. Provocation triggers a reflexive Refine operation that deletes duplicate features from chains, making them interpretable for Transfer. NI Transitivity Alternations result from variant deletion preferences exhibited during Refine. I argue that the NI contexts discussed (Generic NI, Partial NI and Double Object NI) result from different restrictions on phonetic and semantic identity in chain formation. This provides us with a consistent definition of NI Transitivity Alternations across contexts, as well as a new typology that distinguishes NI contexts, rather than incorporating languages.

Fleshing Out and Losing Flesh: The Decomposing Corpse as Narrative Object in American Hardboiled Detective Fiction

This dissertation examines the corpse as an object in and of American hardboiled detective fiction written between 1920 and 1950. I deploy several theoretical frames, including narratology, body-as-text theory, object relations theory, and genre theory, in order to demonstrate the significance of objects, symbols, and things primarily in the clever and crafty work of Dashiell Hammett (1894-1961) and Raymond Chandler (1888-1959), but also touching on the writings of their lesser known accomplices. I construct a literary genealogy of American hardboiled detective fiction originating in the writings of Edgar Allan Poe, compare the contributions of classic or Golden Age detective fiction in England, and describe the socio-economic contexts, particularly the predominance of the “pulps,” that gave birth to the realism of the Hardboiled School. Taking seriously Chandler’s obsession with the art of murder, I engage with how authors pre-empt their readers’ knowledge of the tricks of the trade and manipulate their expectations, as well as discuss the characteristics and effect of the inimitable hardboiled style, its sharpshooting language and deadpan humour. Critical scholarship has rarely addressed the body and figure of the corpse, preferring to focus instead on the machinations of the femme fatale, the performance of masculinity, or the prevalence of violence. I cast new light on the world of hardboiled detective fiction by dissecting the corpse as the object that both motivates and de-composes (or rots away from) the narrative that makes it signify. I treat the corpse as an inanimate object, indifferent to representation, that destabilizes the integrity and self-possession, as well as the ratiocination, of the detective who authors the narrative of how the corpse came to be. The corpse is all deceptive and dangerous surface rather than the container of hidden depths of life and meaning that the detective hopes to uncover and reconstruct. I conclude with a chapter that is both critical denouement and creative writing experiment to reveal the self-reflexive (and at times metafictional) dimensions of hardboiled fiction. My dissertation, too, in the manner of hardboiled fiction, hopes to incriminate my readers as much as enlighten them.

Code pattern analysis of object-oriented programming languages

Code patterns, including programming patterns and design patterns, are good references for programming language feature improvement and software re-engineering. However, to our knowledge, no existing research has attempted to detect code patterns based on code clone detection technology. In this study, we build upon the previous work and propose to detect and analyze code patterns from a collection of open source projects using NiPAT technology. Because design patterns are most closely associated with object-oriented languages, we choose Java and Python projects to conduct our study. The tool we use for detecting patterns is NiPAT, a pattern detecting tool originally developed for the TXL programming language based on the NiCad clone detector. We extend NiPAT for the Java and Python programming languages. Then, we try to identify all the patterns from the pattern report and classify them into several different categories. In the end of the study, we analyze all the patterns and compare the differences between Java and Python patterns.

Experiences with an Object-Oriented, Multi-Stage Language

Metaphor is a multi-stage programming language extension to an imperative, object-oriented language in the style of C# or Java. This paper discusses some issues we faced when applying multi-stage language design concepts to an imperative base language and run-time environment. The issues range from dealing with pervasive references and open code to garbage collection and implementing cross-stage persistence.