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Verbal working memory plays a crucial role in supporting the learning process over the school years. In this study, we investigated the role of the acoustic conditions of school classrooms, specifically reverberation time and babble noise, on second-graders' verbal working memory. A sample of twenty-five second-graders was administered a validated verbal working memory task in two different acoustic conditions, with a time frame of 1 month: Poor acoustic quality (long reverberation time [Long RT] and babble) versus Adequate acoustic quality (short reverberation time [Short RT] and babble). Results showed that the same children were able to remember fewer words and less accurately on the task in a classroom with longer reverberation time and babble compared to one with shorter reverberation time and babble. Moreover, children omitted more words in the recall task in the Poor acoustic quality condition than in the Adequate acoustic quality condition. The results suggested that primary school children's verbal working memory processing is sensitive to variations in the classroom acoustic conditions. These findings offer a research contribution about the importance of adopting a contextual view on cognitive development and insights for the implementation of school interventions in terms of metacognitive work on learning to listen and classroom design. • Primary school children's verbal working memory processing is sensitive to variations in the classroom acoustic conditions. • Results provide support of adopting contextual view on cognitive functioning and development. [ABSTRACT FROM AUTHOR]

In modern railway automatic train protection and automatic train control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. The aim of this work has been developing an innovative localisation algorithm for railway vehicles able to enhance the performances, in terms of speed and position estimation accuracy, of the classical odometry algorithms, such as the ItalianSistema Controllo Marcia Treno(SCMT). The proposed strategy consists of a sensor fusion between the information coming from a tachometer and anInertial Measurements Unit(IMU). The sensor outputs have been simulated through a 3D multibody model of a railway vehicle. The work has provided the development of a custom IMU, designed by ECM S.p.a, in order to meet their industrial and business requirements. The industrial requirements have to be compliant with the European Train Control System (ETCS) standards: the European Rail Traffic Management System (ERTMS), a project developed by the European Union to improve the interoperability among different countries, in particular as regards the train control and command systems, fixes some standard values for the odometric (ODO) performance, in terms of speed and travelled distance estimation. The reliability of the ODO estimation has to be taken into account basing on the allowed speed profiles. The results of the currently used ODO algorithms can be improved, especially in case of degraded adhesion conditions; it has been verified in the simulation environment that the results of the proposed localisation algorithm are always compliant with the ERTMS requirements. The estimation strategy has good performance also under degraded adhesion conditions and could be put on board of high-speed railway vehicles; it represents an accurate and reliable solution. The IMU board is tested via a dedicatedHardware in the Loop(HIL) test rig: it includes an industrial robot able to replicate the motion of the railway vehicle. Through the generated experimental outputs the performances of the innovative localisation algorithm have been evaluated: the HIL test rig permitted to test the proposed algorithm, avoiding expensive (in terms of time and cost) on-track tests, obtaining encouraging results. In fact, the preliminary results show a significant improvement of the position and speed estimation performances compared to those obtained with SCMT algorithms, currently in use on the Italian railway network. [ABSTRACT FROM AUTHOR]

Abstract: This paper investigates the principles of a Cooperative Localization Algorithm for a team of at least three Autonomous Underwater Vehicles (AUVs) with respect to a surface support ship, without the use of Ultra-Short Baseline (USBL). It is assumed that each AUV is equipped with a low-cost Inertial Measurement Unit (IMU), a compass and a depth sensor, but only one of them has a high accuracy navigation sensor such as the Doppler Velocity Log (DVL). The surface boat locates itself by means of Global Positioning System (GPS). Range measurements provided by acoustic modems allow to avoid an unbounded error growth in the position estimate of each AUV. A geometric method, based on a tetrahedral configuration to obtain a deterministic fix for position, is proposed. This method allows to extend the advantages of the use of the DVL to the position estimate of other vehicles not equipped with DVL. The paper addresses also some of the problems related to the limitations of acoustic communication. The algorithm has been implemented and tested in simulations for a fleet of three AUVs and a surface support ship. [Copyright &y& Elsevier]

In modern railway Automatic Train Protection and Automatic Train Control systems, odometry is a safety relevant on-board subsystem which estimates the instantaneous speed and the travelled distance of the train; a high reliability of the odometry estimate is fundamental, since an error on the train position may lead to a potentially dangerous overestimation of the distance available for braking. To improve the odometry estimate accuracy, data fusion of different inputs coming from a redundant sensor layout may be used. Simplified two-dimensional models of railway vehicles have been usually used for Hardware in the Loop test rig testing of conventional odometry algorithms and of on-board safety relevant subsystems (like the Wheel Slide Protection braking system) in which the train speed is estimated from the measures of the wheel angular speed. Two-dimensional models are not suitable to develop solutions like the inertial type localisation algorithms (using 3D accelerometers and 3D gyroscopes) and the introduction of Global Positioning System (or similar) or the magnetometer. In order to test these algorithms correctly and increase odometry performances, a three-dimensional multibody model of a railway vehicle has been developed, using Matlab-Simulink™, including an efficient contact model which can simulate degraded adhesion conditions (the development and prototyping of odometry algorithms involve the simulation of realistic environmental conditions). In this paper, the authors show how a 3D railway vehicle model, able to simulate the complex interactions arising between different on-board subsystems, can be useful to evaluate the odometry algorithm and safety relevant to on-board subsystem performances. [ABSTRACT FROM PUBLISHER]