What absent switch costs and mixing costs during bilingual language comprehension can tell us about language control.

Epub 2019 Mar 28.In the current study, we set out to investigate language control, which is the process that minimizes cross-language interference, during bilingual language comprehension. According to current theories of bilingual language comprehension, language-switch costs, which are a marker for reactive language control, should be observed. However, a closer look at the literature shows that this is not always the case. Furthermore, little to no evidence for language-mixing costs, which are a marker for proactive language control, has been observed in the bilingual language comprehension literature. This is in line with current theories of bilingual language comprehension, as they do not explicitly account for proactive language control. In the current study, we further investigated these two markers of language control and found no evidence for comprehension-based language-switch costs in six experiments, even though other types of switch costs were observed with the exact same setup (i.e., task-switch costs, stimulus modality-switch costs, and production-based language-switch costs). Furthermore, only one out of three experiments showed comprehension-based language-mixing costs, providing the first tentative evidence for proactive language control during bilingual language comprehension. The implications of the absence and occurrence of these costs are discussed in terms of processing speed and parallel language activation. (PsycINFO Database Record (c) 2019 APA, all rights reserved)This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 706128. This research was also supported by grants ANR-11-LABX-0036 (BLRI), ANR-16-CONV-0002 (ILCB), and ANR-11-IDEX-0001-02 from the French National Research Council (ANR)

Using a CLIPS expert system to automatically manage TCP/IP networks and their components

A expert system that can directly manage networks components on a Transmission Control Protocol/Internet Protocol (TCP/IP) network is described. Previous expert systems for managing networks have focused on managing network faults after they occur. However, this proactive expert system can monitor and control network components in near real time. The ability to directly manage network elements from the C Language Integrated Production System (CLIPS) is accomplished by the integration of the Simple Network Management Protocol (SNMP) and a Abstract Syntax Notation (ASN) parser into the CLIPS artificial intelligence language

Contribution of reactive and proactive control to children's working memory performance:Insight from item recall durations in response sequence planning

The present study addressed whether developmental improvement in working memory span task performance relies upon a growing ability to proactively plan response sequences during childhood. Two hundred thirteen children completed a working memory span task in which they used a touchscreen to reproduce orally presented sequences of animal names. Children were assessed longitudinally at 7 time points between 3 and 10 years of age. Twenty-one young adults also completed the same task. Proactive response sequence planning was assessed by comparing recall durations for the 1st item (preparatory interval) and subsequent items. At preschool age, the preparatory interval was generally shorter than subsequent item recall durations, whereas it was systematically longer during elementary school and in adults. Although children mostly approached the task reactively at preschool, they proactively planned response sequences with increasing efficiency from age 7 on, like adults. These findings clarify the nature of the changes in executive control that support working memory performance with age

Cobot Programming for Collaborative Industrial Tasks: An Overview

Collaborative robots (cobots) have been increasingly adopted in industries to facilitate human-robot collaboration. Despite this, it is challenging to program cobots for collaborative industrial tasks as the programming has two distinct elements that are difficult to implement: (1) an intuitive element to ensure that the operations of a cobot can be composed or altered dynamically by an operator, and (2) a human-aware element to support cobots in producing flexible and adaptive behaviours dependent on human partners. In this area, some research works have been carried out recently, but there is a lack of a systematic summary on the subject. In this paper, an overview of collaborative industrial scenarios and programming requirements for cobots to implement effective collaboration is given. Then, detailed reviews on cobot programming, which are categorised into communication, optimisation, and learning, are conducted. Additionally, a significant gap between cobot programming implemented in industry and in research is identified, and research that works towards bridging this gap is pinpointed. Finally, the future directions of cobots for industrial collaborative scenarios are outlined, including potential points of extension and improvement

Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations in the area. Here, we explore Java 8 default methods, which allow interfaces to contain (instance) method implementations. Default methods can ease interface evolution, make certain ubiquitous design patterns redundant, and improve both modularity and maintainability. A focus of this work is to discover, through a scientific approach and a novel technique, situations where developers found these constructs useful and where they did not, and the reasons for each. Although several studies center around assessing new language features, to the best of our knowledge, this kind of construct has not been previously considered. Despite their benefits, we found that developers did not adopt default methods in all situations. Our study consisted of submitting pull requests introducing the language feature to 19 real-world, open source Java projects without altering original program semantics. This novel assessment technique is proactive in that the adoption was driven by an automatic refactoring approach rather than waiting for developers to discover and integrate the feature themselves. In this way, we set forth best practices and patterns of using the language feature effectively earlier rather than later and are able to possibly guide (near) future language evolution. We foresee this technique to be useful in assessing other new language features, design patterns, and other programming idioms