Children Use Non-referential Gestures in Narrative Speech to Mark Discourse Elements Which Update Common Ground

While recent studies have claimed that non-referential gestures (i.e., gestures that do not visually represent any semantic content in speech) are used to mark discourse-new and/or -accessible referents and focused information in adult speech, to our knowledge, no prior investigation has studied the relationship between information structure (IS) and gesture referentiality in children’s narrative speech from a developmental perspective. A longitudinal database consisting of 332 narratives performed by 83 children at two different time points in development was coded for IS and gesture referentiality (i.e., referential and non-referential gestures). Results revealed that at both time points, both referential and non-referential gestures were produced more with information that moves discourse forward (i.e., focus) and predication (i.e., comment) rather than topical or background information. Further, at 7–9 years of age, children tended to use more non-referential gestures to mark focus and comment constituents than referential gestures. In terms of the marking of the newness of discourse referents, non-referential gestures already seem to play a key role at 5–6 years old, whereas referential gestures did not show any patterns. This relationship was even stronger at 7–9 years old. All in all, our findings offer supporting evidence that in contrast with referential gestures, non-referential gestures have been found to play a key role in marking IS, and that the development of this relationship solidifies at a period in development that coincides with a spurt in non-referential gesture production.

Effectiveness Analysis on Human-Machine Information Interaction of Intelligent Highway

Different human-machine collaboration modes and driving simulation tests with the orthogonal method considered are designed for a series of typical intelligent highway landscapes. The feedback of drivers under different interaction modes is evaluated through NASA-LTX questionnaire, driving simulator, eye tracker, and electroencephalograph (EEG). This optimal interaction mode (including voice form, broadcasting timing, and frequency) of each driving assistance scene in CVI (Cooperative Vehicle Infrastructure) environment under the conditions of high and low traffic is determined from subjective and objective perspectives. In accordance with feedback of these subjects on each set scene, the voice information structure of each assistance mode plays the most important role on drivers followed by the broadcasting timing and frequency. These broadcasts which provide good effects include scenarios such as various assistance scenes at curves and an early warning timing at a long-distance trip as well as a high early warning frequency; in addition, as for an exit-tip assistance scenario, a voice mode assistance is preferred; and for various speed assistance scenes, the beep mode is better. Furthermore, it is found that, at a higher traffic level but a short-distance trip, an early warning timing is favored generally for various scenes while under a low traffic level, a long-distance early warning timing is better.

The emergence of Information Structure in child speech: the acquisition of c’est-clefts in French

Constructions marking information structure in French have been widely documented within the constructionist framework. C’est ‘it is’ clefts have been demonstrated to express the focus of the sentence. Nevertheless, it remains unclear how children are able to acquire clefts, and how they develop information structure categories. The aim of this study is to investigate the acquisition of clefts in French through the usage-based framework, to understand (i) whether IS categories emerge gradually like other linguistic categories, and (ii) how children build IS categories. For this, I analysed 256 c’est-clefts produced by three children between age 2 and 3. I show that most early clefts are produced by children with the chunk c’est moi associated with the concrete function of requesting to perform an action themselves. This chunk then becomes a frame with slot, extending the function to other human referents and discourse participants with the function of requesting adults to perform an action. Another large portion of early clefts seems to belong to a frame with slot c’est X whose function is to identify the agent who carried out an action. These findings suggest that the information structure category of focus emerges gradually.

Information structure effects on the processing of nouns and verbs: evidence from event-related brain potentials

Electroencephalographic (EEG) signals can reveal the cost required to deal with information structure mismatches in speech or in text contexts. The present study investigates the costs related to the processing of different associations between the syntactic categories of Noun and Verb and the information categories of Topic and Focus. It is hypothesized that – due to the very nature (respectively, predicative and non-predicative) of verbal and nominal reference – sentences with Topics realized by verbs, and Focuses realized by nouns, should impose greater processing demands, compared to the decoding of nominal Topics and verbal Focuses. Data from event-related potential (ERP) measurements revealed an N400 effect in response to both nouns encoded as Focus and verbs packaged as Topic, confirming that the cost associated with information structure processing follows discourse-driven expectations also with respect to the word-class level.

Counterfactuals with Latent Information

We describe a methodology for making counterfactual predictions in settings where the information held by strategic agents and the distribution of payoff-relevant states of the world are unknown. The analyst observes behavior assumed to be rationalized by a Bayesian model, in which agents maximize expected utility, given partial and differential information about the state. A counterfactual prediction is desired about behavior in another strategic setting, under the hypothesis that the distribution of the state and agents’ information about the state are held fixed. When the data and the desired counterfactual prediction pertain to environments with finitely many states, players, and actions, the counterfactual prediction is described by finitely many linear inequalities, even though the latent parameter, the information structure, is infinite dimensional. (JEL D44, D82, D83)

TARA-Net: A Fusion Network for Detecting Takeaway Rider Accidents

In the emerging business of food delivery, rider traffic accidents raise financial cost and social traffic burden. Although there has been much effort on traffic accident forecasting using temporal-spatial prediction models, none of the existing work studies the problem of detecting the takeaway rider accidents based on food delivery trajectory data. In this article, we aim to detect whether a takeaway rider meets an accident on a certain time period based on trajectories of food delivery and riders’ contextual information. The food delivery data has a heterogeneous information structure and carries contextual information such as weather and delivery history, and trajectory data are collected as a spatial-temporal sequence. In this article, we propose a TakeAway Rider Accident detection fusion network TARA-Net to jointly model these heterogeneous and spatial-temporal sequence data. We utilize the residual network to extract basic contextual information features and take advantage of a transformer encoder to capture trajectory features. These embedding features are concatenated into a pyramidal feed-forward neural network. We jointly train the above three components to combine the benefits of spatial-temporal trajectory data and sparse basic contextual data for early detecting traffic accidents. Furthermore, although traffic accidents rarely happen in food delivery, we propose a sampling mechanism to alleviate the imbalance of samples when training the model. We evaluate the model on a transportation mode classification dataset Geolife and a real-world Ele.me dataset with over 3 million riders. The experimental results show that the proposed model is superior to the state-of-the-art.

Analysis of methodological approaches to the construction of dynamic systems of investment in information development

The object of research is theoretical and methodological approaches to mathematical modelling of dynamic nonlinear systems to ensure dynamic management of the investment process of information development of enterprises. Methodological aspects of building dynamic investment systems, maximizing the effectiveness of system interaction in information development are considered. One of the most problematic places is the formulation of the optimal approach to the methods of system analysis of decision management. The paper provides an opportunity to solve a wide range of problems, related to the flexible management of investment projects in the implementation of information technology. The study used the economic component of the formation of information resources, which contains an integral investment component of the information system. This is due to the fact that the proposed discreteness of this approach in the complex dynamics of the value of the information system contains partial estimates. Therefore, there should be a scheme of constant review of its value, which contains a dynamic component of the investment value of the information system with properties. The axiomatic approach was used in one of the most common approaches in the formal study of systems. The peculiarity is that the model is based on certain basic assumptions that do not require theoretical justification – on axioms. The study identified the main characteristics of the dynamic investment component of the system. Investments will have the properties of assessing information flows as part of information development. In particular, the research used approaches to modelling many solutions of the investment resources management process. The stages of modelling the process of dynamics and state of the system, implementation of the information support system are determined. This provides an opportunity to identify and assess the stages of investment, analysis of key risks and existing opportunities, defining strategies and methods of response, system typing. As well as the development and implementation of action plans to minimize the variability of investment areas and information structure.

Memetics as informational difference: offering an information-centric conception of memes

PurposeInformation scientists may find value in studying cultural information evolution and information diffusion through memetics. Information studies in memetics have often found datafication in memetics research difficult. Meanwhile, current memetic scholarship elsewhere is abundant in data due to their focus on Internet artifacts. This paper offers a way to close the datafication gap for information researchers by associating information data with “differences” between memetic documents.Design/methodology/approachThis work offers a joint theory and methodology invested in information-oriented memetics. This methodology of differences is developed from a content analysis of difference on a collection of images with visual similarities.FindingsThe authors find that this kind of analysis provides a heuristic method for quantitatively bounding where one meme ends and another begins. The authors also find that this approach helps describe the dynamics of memetic media in such a way that the authors can datafy information or cultural evolution more clearly.Originality/valueHere the authors offer an approach for studying cultural information evolution through the study of memes. In doing so, the authors forward a methodology of difference which leverages content analysis in order to outline how it functions practically. The authors propose a quantitative methodology to assess differences between versions of document contents in order to examine what a particular meme is. The authors also move toward showing the information structure which defines a meme.