Object and handling handshapes in 11 sign languages: towards a typology of the iconic use of the hands

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Victoria Nyst ◽  
Marta Morgado ◽  
Timothy Mac Hadjah ◽  
Marco Nyarko ◽  
Mariana Martins ◽  
...  
Keyword(s):  
Significant Variation ◽  
Linguistic Variation ◽  
Large Set ◽  
Human Language ◽  
Sign Languages ◽  
Data Set ◽  
European Origin ◽  
Use Of Space ◽  
Fine Grained ◽  
Iconic Signs

Abstract This article looks at cross-linguistic variation in lexical iconicity, addressing the question of to what extent and how this variation is patterned. More than in spoken languages, iconicity is highly frequent in the lexicons of sign languages. It is also highly complex, in that often multiple motivated components jointly shape an iconic lexeme. Recent typological research on spoken languages finds tentative iconic patterning in a large number of basic lexical items, underlining once again the significance of iconicity for human language. The uncontested and widespread use of iconicity found in the lexicons of sign languages enables us to take typological research into lexical iconicity to the next level. Indeed, previous studies have shown cross-linguistic variation in: a) the use of embodying and handling handshapes in sign languages (mostly of European origin) and b) the frequency of space-based size depiction in African and European sign languages. The two types of variation may be interrelated, as handling handshapes may use space-based size depiction. In this study, we first replicate earlier studies on the distribution of embodying and handling handshapes, this time in a data set consisting of a relatively large set of sign languages (n = 11), most of which are used in Africa. The results confirm significant variation across these sign languages. These findings are then compared to the use of space-based size depiction, revealing that these patterns independently from the distribution of embodying/handling handshapes. We argue that the results call for expanding typological studies on representational strategies in iconic signs beyond the now relatively well studied instrument/manipulation alternation. Fine-grained analyses on a multitude of iconic features in signs are likely to reveal cross-linguistic variation in iconic tendencies in SL lexicons.

scholarly journals Body as subject

2007 ◽  
Vol 43 (3) ◽  
pp. 531-563 ◽  
Author(s):  
IRIT MEIR ◽  
CAROL A. PADDEN ◽  
MARK ARONOFF ◽  
WENDY SANDLER
Keyword(s):  
The Body ◽  
Human Language ◽  
States Of Affairs ◽  
Sign Languages ◽  
Verb Agreement ◽  
Lexical Structure ◽  
Privileged Status ◽  
The Subject ◽  
Subject Agreement ◽  
Iconic Signs

The notion of subject in human language has a privileged status relative to other arguments. This special status is manifested in the behavior of subjects at the morphological, syntactic, semantic and discourse levels. Here we present evidence that subjects have a privileged status at the lexical level as well, by analyzing lexicalization patterns of verbs in three different sign languages. Our analysis shows that the sub-lexical structure of iconic signs denoting states of affairs in these languages manifests an inherent pattern of form–meaning correspondence: the signer's body consistently represents one argument of the verb, the subject. The hands, moving in relation to the body, represent all other components of the event – including all other arguments. This analysis shows that sign languages provide novel evidence in support of the centrality of the notion of subject in human language. It also solves a typological puzzle about the apparent primacy of object in sign language verb agreement, a primacy not usually found in spoken languages, in which subject agreement generally ranks higher. Our analysis suggests that the subject argument is represented by the body and is part of the lexical structure of the verb. Because it is always inherently represented in the structure of the sign, the subject is more basic than the object, and tolerates the omission of agreement morphology.

scholarly journals Cross-linguistic variation in space-based distance for size depiction in the lexicons of six sign languages

2018 ◽  
Vol 21 (2) ◽  
pp. 350-379 ◽  
Author(s):  
Victoria Nyst
Keyword(s):  
West African ◽  
Linguistic Variation ◽  
African Origin ◽  
Sign Languages ◽  
European Origin ◽  
African Languages ◽  
European Languages ◽  
Frequency Of Use ◽  
Representation Technique ◽  
Representation Techniques

Abstract This paper presents a semiotic study of the distribution of a type of size depiction in lexical signs in six sign languages. Recently, a growing number of studies are focusing on the distribution of two representation techniques, i.e. the use of entity handshapes and handling handshapes for the depiction of hand-held tools (e.g. Ortega et al. 2014). Padden et al. (2013) find that there is cross-linguistic variation in the use of this pair of representation techniques. This study looks at variation in a representation technique that has not been systematically studied before, i.e. the delimitation of a stretch of space to depict the size of a referent, or space-based distance for size depiction. It considers the question whether the cross-linguistic variation in the use of this representation technique is governed by language-specific patterning as well (cf. Padden et al. 2013). This study quantifies and compares the occurrence of space-based distance for size depiction in the lexicons of six sign languages, three of Western European origin, and three of West African origin. It finds that sign languages differ significantly from each other in their frequency of use of this depiction type. This result thus corroborates that the selection and distribution of representation techniques does not solely depend on features of the depicted image, but also on language-specific patterning in the distribution of representation techniques, and it adds another dimension of iconic depiction in which sign languages may vary from each other (in addition to the entity/handling handshape distinction). Moreover, the results appear to be areally defined, with the three European languages using this representation technique significantly more often than the three African languages.

Molecular Views of Ice-Embedded Lumbricus Terrestris Erythrocruorin Obtained By Invariant Classification

1990 ◽  
Vol 48 (1) ◽  
pp. 450-451
Author(s):  
Michael schatz ◽  
Joachim Jäger ◽  
Marin van Heel
Keyword(s):  
Image Interpretation ◽  
Lumbricus Terrestris ◽  
Reference Image ◽  
Large Set ◽  
Multivariate Statistical ◽  
Data Set ◽  
Low Contrast ◽  
Negative Stain ◽  
Reference Images ◽  
Statistical Resolution

Lumbricus terrestris erythrocruorin is a giant oxygen-transporting macromolecule in the blood of the common earth worm (worm "hemoglobin"). In our current study, we use specimens (kindly provided by Drs W.E. Royer and W.A. Hendrickson) embedded in vitreous ice (1) to avoid artefacts encountered with the negative stain preparation technigue used in previous studies (2-4).Although the molecular structure is well preserved in vitreous ice, the low contrast and high noise level in the micrographs represent a serious problem in image interpretation. Moreover, the molecules can exhibit many different orientations relative to the object plane of the microscope in this type of preparation. Existing techniques of analysis requiring alignment of the molecular views relative to one or more reference images often thus yield unsatisfactory results.We use a new method in which first rotation-, translation- and mirror invariant functions (5) are derived from the large set of input images, which functions are subsequently classified automatically using multivariate statistical techniques (6). The different molecular views in the data set can therewith be found unbiasedly (5). Within each class, all images are aligned relative to that member of the class which contributes least to the classes′ internal variance (6). This reference image is thus the most typical member of the class. Finally the aligned images from each class are averaged resulting in molecular views with enhanced statistical resolution.

scholarly journals Calibration of a Multiphase Model Based on a Comprehensive Data Set for a Normal Strength Concrete

Materials ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 791 ◽  
Author(s):  
Peter Gamnitzer ◽  
Martin Drexel ◽  
Andreas Brugger ◽  
Günter Hofstetter
Keyword(s):  
Water Content ◽  
Accurate Determination ◽  
Autogenous Shrinkage ◽  
Shrinkage Strain ◽  
Desorption Isotherm ◽  
Multiphase Model ◽  
Large Set ◽  
Creep Tests ◽  
Data Set ◽  
Water Desorption

Hygro-thermo-chemo-mechanical modelling of time-dependent concrete behavior requires the accurate determination of a large set of parameters. In this paper, the parameters of a multiphase model are calibrated based on a comprehensive set of experiments for a particular concrete of grade C30/37. The experiments include a calorimetry test, tests for age-dependent mechanical properties, tests for determining the water desorption isotherm, shrinkage tests, and compressive creep tests. The latter two were performed on sealed and unsealed specimens with accompanying mass water content measurements. The multiphase model is based on an effective stress formulation. It features a porosity-dependent desorption isotherm, taking into account the time-dependency of the desorption properties. The multiphase model is shown to yield excellent results for the evolutions of the mechanical parameters. The evolution of the autogenous shrinkage strain and evolutions of the creep compliances for loading at concrete ages of 2 days, 7 days, and 28 days are well predicted together with the respective mass water content evolution. This also holds for the evolution of the drying shrinkage strain, at least for moderate drying up to one year. However, it will be demonstrated that for longer drying times further conceptual thoughts concerning the coupled representation of shrinkage and creep are required.

Mapping variation in Basque: The BiV database

2019 ◽  
Vol 23 (2) ◽  
pp. 347-374
Author(s):  
Beatriz Fernández ◽  
Ane Berro ◽  
Iñigo Urrestarazu ◽  
Itziar Orbegozo
Keyword(s):  
Open Access ◽  
Research Group ◽  
Linguistic Variation ◽  
Online Database ◽  
Dialectal Variation ◽  
Fine Grained ◽  
User Friendly

Abstract The aim of this paper is to present the Euskara Bariazioan/Basque in Variation (BiV) database, a project launched by the Basque and Beyond (Bas&Be) research group. This open-access online database, available in both Basque and English versions, is intended to facilitate research on Basque morphosyntactic features that show cross-dialectal variation. Based on data obtained from questionnaires, the BiV provides the user with a description of each feature together with illustrative examples, and accompanies each entry with a map graphically depicting the distribution of variation. The resulting fine-grained picture of the distribution of morphosyntactic phenomena across Basque varieties has the ultimate goal of improving our understanding of the systematicities and connections that underlie variation. Thanks to its user-friendly format, the database can be used easily by anyone who is interested in Basque morphosyntax in particular and cross-linguistic variation in general. The results obtained thus far show that while some features have the same distribution across Basque varieties as that previously reported, others are spreading and thus have a wider geographical presence than has been described in the literature.

scholarly journals Recognition and Classification of Broiler Droppings Based on Deep Convolutional Neural Network

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Jintao Wang ◽  
Mingxia Shen ◽  
Longshen Liu ◽  
Yi Xu ◽  
Cedric Okinda
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Digestive Disease ◽  
Deep Convolutional Neural Network ◽  
Mean Average Precision ◽  
Average Precision ◽  
Deep Convolutional Neural Networks ◽  
Data Set ◽  
Fine Grained ◽  
Digestive Diseases

Digestive diseases are one of the common broiler diseases that significantly affect production and animal welfare in broiler breeding. Droppings examination and observation are the most precise techniques to detect the occurrence of digestive disease infections in birds. This study proposes an automated broiler digestive disease detector based on a deep Convolutional Neural Network model to classify fine-grained abnormal broiler droppings images as normal and abnormal (shape, color, water content, and shape&water). Droppings images were collected from 10,000 25-35-day-old Ross broiler birds reared in multilayer cages with automatic droppings conveyor belts. For comparative purposes, Faster R-CNN and YOLO-V3 deep Convolutional Neural Networks were developed. The performance of YOLO-V3 was improved by optimizing the anchor box. Faster R-CNN achieved 99.1% recall and 93.3% mean average precision, while YOLO-V3 achieved 88.7% recall and 84.3% mean average precision on the testing data set. The proposed detector can provide technical support for the detection of digestive diseases in broiler production by automatically and nonintrusively recognizing and classifying chicken droppings.

Practical Attribute-Based Conjunctive Keyword Search Scheme

2019 ◽  
Vol 63 (8) ◽  
pp. 1203-1215 ◽  
Author(s):  
Yang Chen ◽  
Wenmin Li ◽  
Fei Gao ◽  
Kaitai Liang ◽  
Hua Zhang ◽  
...  
Keyword(s):  
Keyword Search ◽  
Inner Product ◽  
Real World Data ◽  
Data Set ◽  
Fine Grained ◽  
Keyword Guessing Attack ◽  
Secure Search ◽  
Data Owner ◽  
Cryptographic Primitive ◽  
Guessing Attack

Abstract To date cloud computing may provide considerable storage and computational power for cloud-based applications to support cryptographic operations. Due to this benefit, attribute-based keyword search (ABKS) is able to be implemented in cloud context in order to protect the search privacy of data owner/user. ABKS is a cryptographic primitive that can provide secure search services for users but also realize fine-grained access control over data. However, there have been two potential problems that prevent the scalability of ABKS applications. First of all, most of the existing ABKS schemes suffer from the outside keyword guessing attack (KGA). Second, match privacy should be considered while supporting multi-keyword search. In this paper, we design an efficient method to combine the keyword search process in ABKS with inner product encryption and deploy several proposed techniques to ensure the flexibility of retrieval mode, the security and efficiency of our scheme. We later put forward an attribute-based conjunctive keyword search scheme against outside KGA to solve the aforementioned problems. We provide security notions for two types of adversaries and our construction is proved secure against chosen keyword attack and outside KGA. Finally, all-side simulation with real-world data set is implemented for the proposed scheme, and the results of the simulation show that our scheme achieves stronger security without yielding significant cost of storage and computation.

scholarly journals Dynamic spatio-temporal generation of large-scale synthetic gridded precipitation: with improved spatial coherence of extremes

2019 ◽  
Vol 34 (9) ◽  
pp. 1369-1383 ◽  
Author(s):  
Dirk Diederen ◽  
Ye Liu
Keyword(s):  
Large Scale ◽  
Spatial Coherence ◽  
Original Data ◽  
Return Level ◽  
Data Sets ◽  
Large Set ◽  
Precipitation Data ◽  
Data Set ◽  
Spatio Temporal ◽  
Synthetic Precipitation

Abstract With the ongoing development of distributed hydrological models, flood risk analysis calls for synthetic, gridded precipitation data sets. The availability of large, coherent, gridded re-analysis data sets in combination with the increase in computational power, accommodates the development of new methodology to generate such synthetic data. We tracked moving precipitation fields and classified them using self-organising maps. For each class, we fitted a multivariate mixture model and generated a large set of synthetic, coherent descriptors, which we used to reconstruct moving synthetic precipitation fields. We introduced randomness in the original data set by replacing the observed precipitation fields in the original data set with the synthetic precipitation fields. The output is a continuous, gridded, hourly precipitation data set of a much longer duration, containing physically plausible and spatio-temporally coherent precipitation events. The proposed methodology implicitly provides an important improvement in the spatial coherence of precipitation extremes. We investigate the issue of unrealistic, sudden changes on the grid and demonstrate how a dynamic spatio-temporal generator can provide spatial smoothness in the probability distribution parameters and hence in the return level estimates.

scholarly journals To use or not to use: Feature selection for sentiment analysis of highly imbalanced data

2017 ◽  
Vol 24 (1) ◽  
pp. 3-37 ◽  
Author(s):  
SANDRA KÜBLER ◽  
CAN LIU ◽  
ZEESHAN ALI SAYYED
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Sentiment Analysis ◽  
Information Gain ◽  
Binary Classification ◽  
Small Subset ◽  
Large Set ◽  
Learning Approaches ◽  
Selection Methods ◽  
Data Set

AbstractWe investigate feature selection methods for machine learning approaches in sentiment analysis. More specifically, we use data from the cooking platform Epicurious and attempt to predict ratings for recipes based on user reviews. In machine learning approaches to such tasks, it is a common approach to use word or part-of-speech n-grams. This results in a large set of features, out of which only a small subset may be good indicators for the sentiment. One of the questions we investigate concerns the extension of feature selection methods from a binary classification setting to a multi-class problem. We show that an inherently multi-class approach, multi-class information gain, outperforms ensembles of binary methods. We also investigate how to mitigate the effects of extreme skewing in our data set by making our features more robust and by using review and recipe sampling. We show that over-sampling is the best method for boosting performance on the minority classes, but it also results in a severe drop in overall accuracy of at least 6 per cent points.

scholarly journals The Impact of Soda Taxes: Pass-Through, Tax Avoidance, and Nutritional Effects

2020 ◽  
pp. 002224372096940 ◽  
Author(s):  
Stephan Seiler ◽  
Anna Tuchman ◽  
Song Yao
Keyword(s):  
Average Rate ◽  
Tax Avoidance ◽  
Policy Decision ◽  
Large Set ◽  
Data Set ◽  
Sweetened Beverages ◽  
Geographic Coverage ◽  
Pass Through ◽  
The Impact ◽  
The City

The authors analyze the impact of a tax on sweetened beverages using a unique data set of prices, quantities sold, and nutritional information across several thousand taxed and untaxed beverages for a large set of stores in Philadelphia and its surrounding area. The tax is passed through at an average rate of 97%, leading to a 34% price increase. Demand in the taxed area decreases by 46% in response to the tax. Cross-shopping to stores outside of Philadelphia offsets more than half of the reduction in sales in the city and decreases the net reduction in sales of taxed beverages to only 22%. There is no significant substitution to bottled water and modest substitution to untaxed natural juices. The authors show that tax avoidance through cross-shopping severely constrains revenue generation and nutritional improvement, thus making geographic coverage an important policy decision.

Sign in / Sign up

Export Citation Format

Share Document