scholarly journals Aggressive reduplication and dissimilation in Sundanese

2020 ◽  
Vol 2 (5) ◽  
Author(s):  
Juliet Stanton
Keyword(s):  
Long Distance ◽  
Local Contexts ◽  
Non Local ◽  
Statistical Trends

Most cases of long-distance consonant dissimilation can be characterized as local (occurring across a vowel) or unbounded (occurring at all distances). The only known exception is rhotic dissimilation in Sundanese (Cohn 1992; Bennett 2015a,b), which applies in certain non-local contexts only. Following a suggestion by Zuraw (2002:433), I show that the pattern can be analyzed in a co-occurrence-based framework (Suzuki 1998) by invoking two unbounded co-occurrence constraints, *[r]…[r] and *[l]…[l], whose effects in local contexts are obscured by a drive for identity between adjacent syllables. Statistical trends in the lexicon are consistent with this analysis. I compare the predictions of this analysis to those of Bennett’s (2015a,b) and suggest that the present proposal is preferable.

scholarly journals Non-Local and Multi-Scale Mechanisms for Image Inpainting

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3281
Author(s):  
Xu He ◽  
Yong Yin
Keyword(s):  
Markov Random Fields ◽  
Receptive Fields ◽  
Image Inpainting ◽  
Long Distance ◽  
Visual Appearance ◽  
Fine Grained ◽  
Multi Scale ◽  
Non Local ◽  
Relationship Of

Recently, deep learning-based techniques have shown great power in image inpainting especially dealing with squared holes. However, they fail to generate plausible results inside the missing regions for irregular and large holes as there is a lack of understanding between missing regions and existing counterparts. To overcome this limitation, we combine two non-local mechanisms including a contextual attention module (CAM) and an implicit diversified Markov random fields (ID-MRF) loss with a multi-scale architecture which uses several dense fusion blocks (DFB) based on the dense combination of dilated convolution to guide the generative network to restore discontinuous and continuous large masked areas. To prevent color discrepancies and grid-like artifacts, we apply the ID-MRF loss to improve the visual appearance by comparing similarities of long-distance feature patches. To further capture the long-term relationship of different regions in large missing regions, we introduce the CAM. Although CAM has the ability to create plausible results via reconstructing refined features, it depends on initial predicted results. Hence, we employ the DFB to obtain larger and more effective receptive fields, which benefits to predict more precise and fine-grained information for CAM. Extensive experiments on two widely-used datasets demonstrate that our proposed framework significantly outperforms the state-of-the-art approaches both in quantity and quality.

scholarly journals Branching Space-Times

2021 ◽  
Author(s):  
Nuel Belnap ◽  
Thomas Müller ◽  
Tomasz Placek
Keyword(s):  
Single Case ◽  
Formal Analysis ◽  
Rigorous Theory ◽  
Quantum Non Locality ◽  
Foundations Of Physics ◽  
Local Contexts ◽  
Rigorous Framework ◽  
Non Local ◽  
Spatio Temporal ◽  
Non Locality

This book develops a rigorous theory of indeterminism as a local and modal concept. Its crucial insight is that our world contains events or processes with alternative, really possible outcomes. The theory aims at clarifying what this assumption involves, and it does it in two ways. First, it provides a mathematically rigorous framework for local and modal indeterminism. Second, we support that theory by spelling out the philosophically relevant consequences of this formulation and by showing its fruitful applications in metaphysics. To this end, we offer a formal analysis of modal correlations and of causation, which is applicable in indeterministic and non-local contexts as well. We also propose a rigorous theory of objective single-case probabilities, intended to represent degrees of possibility. In a third step, we link our theory to current physics, investigating how local and modal indeterminism relates to issues in the foundations of physics, in particular, quantum non-locality and spatio-temporal relativity. The book also ventures into the philosophy of time, showing how the theory’s resources can be used to explicate the dynamic concept of the past, present, and future based on local indeterminism.

Relativized Locality: Phases and Tiers in Long-Distance Allomorphy in Armenian

2021 ◽  
pp. 1-83
Author(s):  
Hossep Dolatian ◽  
Peter Guekguezian
Keyword(s):  
Morphological Features ◽  
Formal Property ◽  
Long Distance ◽  
Non Local ◽  
Morphological Processes ◽  
The Cross

Abstract Linguistic processes tend to respect locality constraints. In this paper, we analyze the distribution of conjugation classes in Armenian verbs. We analyze a type of Tense allomorphy which applies across these classes. On the surface, we show that this allomorphy is long-distance. Specifically, it is sensitive to the interaction of multiple morphemes that are neither linearly nor structurally adjacent. However, we argue that this allomorphy respects ‘relativized adjacency’ (Toosarvandani 2016) or tier-based locality (Aksënova, Graf, and Moradi 2016). While not surface-local, the interaction in Armenian verbs is local on a tier projected from morphological features. This formal property of tier-based locality is substantively manifested as phase-based locality in Armenian (cf. Marvin 2002). In addition to being well-studied computationally, tier-based locality allows us to capture superficially non-local morphological processes while respecting the cross-linguistic tendency of locality. We speculate that tier-based locality is a cross-linguistic tendency in long-distance allomorphy, while phase-based locality is not necessarily so.

Anaphor binding

2019 ◽  
pp. 289-302
Author(s):  
Jan Terje Faarlund
Keyword(s):  
Noun Phrases ◽  
Long Distance ◽  
Subordinate Clauses ◽  
Binding Domains ◽  
Reflexive Pronoun ◽  
Infinitival Clauses ◽  
Verbal Content ◽  
Non Local ◽  
Small Clauses ◽  
Local Binding

Scandinavian has a reflexive pronoun and a reflexive possessive for the 3rd person, and a reciprocal pronoun for all persons. Regular binding domains are finite and non-finite clauses, small clauses, and noun phrases with a verbal content and a genitive ‘agent’. There are also less expected binding relations within NPs, possibly involving an invisible binder. Within VP an indirect object may bind a direct object. Even non-c-commanding binders within VP do exist. Non-local binding into small clauses and infinitival clauses is frequent. Some varieties, especially Norwegian, also allow long distance binding, i.e. binding into finite subordinate clauses. At this point, there is a great deal of variation in acceptability, and definite rules are hard to identify.

A typology of non-local reflexives in the Scandinavian languages

2011 ◽  
Vol 34 (2) ◽  
pp. 157-178 ◽  
Author(s):  
Tania E. Strahan
Keyword(s):  
Relative Clause ◽  
Functional Structure ◽  
Functional Grammar ◽  
Long Distance ◽  
Second Person ◽  
Lexical Functional Grammar ◽  
Person Pronoun ◽  
Path Constraints ◽  
Non Local ◽  
Inside Out

The Scandinavian languages are very closely related but also vary syntactically in interesting ways, making this family useful in the study of typology variation. In this paper the issue of non-local reflexives, or ‘long-distance reflexives’ (LDR) is investigated. New LDR data from the Scandinavian languages is presented to show that the Binding Conditions cannot account for the variation in LDR in these languages, since the range of domains that LDR may or may not occur in in each variety varies non-hierarchically. For instance, LDR in Icelandic may be bound out of a finite complement clause but not out of a relative clause, while the reverse is true in most Norwegian dialects. Faroese allows LDR out of both clause types, but many dialects do not allow a second person pronoun to co-occur in a sentence containing LDR, which does not generally affect Icelandic or Norwegian LDR. An extension of Dalrymple's (1993) typology of anaphora, which is set within the framework of Lexical-Functional Grammar, can account for this data, using a combination of inside-out and outside-in functional uncertainty equations, on- and off-path constraints and positive and negative constraints, all of which refer to elements (potentially) found in functional-structure.

scholarly journals Antecedent-based approach to binding in Icelandic and Faroese

Nordlyd ◽  
2011 ◽  
Vol 37 ◽  
pp. 151 ◽  
Author(s):  
Tania E. Strahan
Keyword(s):  
Standard Approach ◽  
Functional Grammar ◽  
Long Distance ◽  
Lexical Functional Grammar ◽  
Non Local ◽  
Inside Out

<p>This paper examines the standard approach to long-distance reflexives within the Lexical-Functional Grammar framework. This approach defines the binding relation between a reflexive and its non-local antecedent by prescribing the type of syntactic elements which must and must not occur along the path from the reflexive to its antecedent. However, evidence from the Insular Scandinavian languages suggests that the binding relation should be expressed as positive and negative constraints on the path from the antecedent to the reflexive. In other words, I suggest that long-distance reflexives in Icelandic and Faroese are governed by outside-in functional uncertainty, not inside-out functional uncertainty, as is standardly assumed.</p>

scholarly journals Nonlinear (MARS) modeling of long-term variations of surface UV-B radiation as revealed from the analysis of Belsk, Poland data for the period 1976–2000

2003 ◽  
Vol 21 (8) ◽  
pp. 1887-1896 ◽  
Author(s):  
J. W. Krzyścin
Keyword(s):  
Ordinary Least Squares ◽  
Statistical Technique ◽  
Multivariate Adaptive Regression Splines ◽  
Atmospheric Composition ◽  
Total Solar Radiation ◽  
Long Distance ◽  
Least Squares Fit ◽  
Non Local ◽  
Global Atmospheric Circulation ◽  
High Level

Abstract. A new, powerful statistical technique, multivariate adaptive regression splines (MARS), is applied to reproduce monthly fractional deviations of UV-B doses over Belsk, Poland, during the snowless (May–October) part of the year in the period 1976–2000. Two kinds of regressors were used: local ones (total ozone, percentage of sky covered by low-, mid-, high-level clouds or total solar radiation over Belsk) and non-local ones, i.e. those describing the long-distance forcings on the surface UV-B due to changes in the global atmospheric circulation. Standard indices of the Quasi-Biennial, North Atlantic, El Niño-Southern Oscillations, and the 11-year solar activity were used as non-local regressors. The results there indicate that the MARS procedure is able to reproduce the observed year-to-year and decadal oscillations in the UV data. The MARS model yields better model-observation agreement than an ordinary least-squares fit based on the same set of regressors. It is found that MARS is capable of handling interactions between the local and non-local regressors, suggesting a possible nonlinear nature of connections between variables characterizing the atmospheric transparency over Belsk and the long-distance forcings. MARS enables a reconstruction of the surface UV-B variations over any site based on the cloud and ozone data presently stored on web pages.Key words. Atmospheric composition and structure (aerosols and particles; biosphere-atmosphere interactions)

scholarly journals Spatial externality and indeterminacy

2019 ◽  
Vol 14 (1) ◽  
pp. 102
Author(s):  
Emmanuelle Augeraud-Véron ◽  
Arnaud Ducrot
Keyword(s):  
Existence And Uniqueness ◽  
Supply And Demand ◽  
Uniqueness Of Solutions ◽  
Long Distance ◽  
Gaussian Kernels ◽  
Demand Curves ◽  
Uniqueness Of The Solution ◽  
Non Local ◽  
Spatial Externality ◽  
The Impact

We study conditions for existence and uniqueness of solutions in some space-structured economic models with long-distance interactions between locations. The solution of these models satisfies non local equations, in which the interactions are modeled by convolution terms. Using properties of the spectrum location obtained by studying the characteristic equation, we derive conditions for the existence and uniqueness of the solution. This enables us to characterize the degree of indeterminacy of the system being considered. We apply our methodology to a theoretical one-sector growth model with increasing returns, which takes into account technological interdependencies among countries that are modeled by spatial externalities. When symmetric interaction kernels are considered, we prove that conditions for which indeterminacy occurs are the same as the ones needed when no interactions are taken into account. For Gaussian kernels, we study the impact of the standard deviation parameter on the degree of indeterminacy. We prove that when some asymmetric kernels are considered, indeterminacy can occur with classical assumptions on supply and demand curves.

Theoretical investigations on the non-local effect in a long-distance Brillouin optical time-domain analyzer based on bi-directional Raman amplification

2012 ◽  
Vol 14 (4) ◽  
pp. 045202 ◽  
Author(s):  
Xin-Hong Jia ◽  
Yun-Jiang Rao ◽  
Zi-Nan Wang ◽  
Wei-Li Zhang ◽  
Zeng-Ling Ran ◽  
...  
Keyword(s):  
Time Domain ◽  
Local Effect ◽  
Raman Amplification ◽  
Long Distance ◽  
Theoretical Investigations ◽  
Non Local ◽  
Optical Time

scholarly journals An Improved Deep Residual Network Prediction Model for the Early Diagnosis of Alzheimer’s Disease

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4182
Author(s):  
Haijing Sun ◽  
Anna Wang ◽  
Wenhui Wang ◽  
Chen Liu
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Diagnosis ◽  
Spatial Information ◽  
Feature Space ◽  
Attention Mechanism ◽  
Residual Network ◽  
Long Distance ◽  
Distance Correlation ◽  
Non Local

The early diagnosis of Alzheimer’s disease (AD) can allow patients to take preventive measures before irreversible brain damage occurs. It can be seen from cross-sectional imaging studies of AD that the features of the lesion areas in AD patients, as observed by magnetic resonance imaging (MRI), show significant variation, and these features are distributed throughout the image space. Since the convolutional layer of the general convolutional neural network (CNN) cannot satisfactorily extract long-distance correlation in the feature space, a deep residual network (ResNet) model, based on spatial transformer networks (STN) and the non-local attention mechanism, is proposed in this study for the early diagnosis of AD. In this ResNet model, a new Mish activation function is selected in the ResNet-50 backbone to replace the Relu function, STN is introduced between the input layer and the improved ResNet-50 backbone, and a non-local attention mechanism is introduced between the fourth and the fifth stages of the improved ResNet-50 backbone. This ResNet model can extract more information from the layers by deepening the network structure through deep ResNet. The introduced STN can transform the spatial information in MRI images of Alzheimer’s patients into another space and retain the key information. The introduced non-local attention mechanism can find the relationship between the lesion areas and normal areas in the feature space. This model can solve the problem of local information loss in traditional CNN and can extract the long-distance correlation in feature space. The proposed method was validated using the ADNI (Alzheimer’s disease neuroimaging initiative) experimental dataset, and compared with several models. The experimental results show that the classification accuracy of the algorithm proposed in this study can reach 97.1%, the macro precision can reach 95.5%, the macro recall can reach 95.3%, and the macro F1 value can reach 95.4%. The proposed model is more effective than other algorithms.

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