Almost sure invariance principle for random piecewise expanding maps

We prove a fiberwise almost sure invariance principle for random piecewise expanding transformations in one and higher dimensions using recent developments on martingale techniques

Dynamic Composite Data Physicalization Using Wheeled Micro-Robots

This paper introduces dynamic composite physicalizations, a new class of physical visualizations that use collections of self-propelled objects to represent data. Dynamic composite physicalizations can be used both to give physical form to well-known interactive visualization techniques, and to explore new visualizations and interaction paradigms. We first propose a design space characterizing composite physicalizations based on previous work in the fields of Information Visualization and Human Computer Interaction. We illustrate dynamic composite physicalizations in two scenarios demonstrating potential benefits for collaboration and decision making, as well as new opportunities for physical interaction. We then describe our implementation using wheeled micro-robots capable of locating themselves and sensing user input, before discussing limitations and opportunities for future work

A neural-network-based model predictive control of three-phase inverter with an output LC Filter

Model predictive control (MPC) has become one of the well-established modern control methods for three-phase inverters with an output $LC$ filter, where a high-quality voltage with low total harmonic distortion (THD) is needed. Although it is an intuitive controller, easy to understand and implement, it has the significant disadvantage of requiring a large number of online calculations for solving the optimization problem. On the other hand, the application of model-free approaches such as those based on artificial neural networks approaches is currently growing rapidly in the area of power electronics and drives. This paper presents a new control scheme for a two-level converter based on combining MPC and feed-forward ANN, with the aim of getting lower THD and improving the steady and dynamic performance of the system for different types of loads. First, MPC is used, as an expert, in the training phase to generate data required for training the proposed neural network. Then, once the neural network is fine-tuned, it can be successfully used online for voltage tracking purpose, without the need of using MPC. The proposed ANN-based control strategy is validated through simulation, using MATLAB/Simulink tools, taking into account different loads conditions. Moreover, the performance of the ANN-based controller is evaluated, on several samples of linear and non-linear loads under various operating conditions, and compared to that of MPC, demonstrating the excellent steady-state and dynamic performance of the proposed ANN-based control strategy

Suggesting a Service Research Agenda in Sport Tourism: Working Experience(s) into Business Models

Purpose: Business models describe how value is delivered to customers/consumers. When considering sport tourism, the focus on delivering value shifts to the sport experiences being offered in a destination. The purpose of this paper was to fulfil a void that links concept of business models to the area of sport tourism management by integrating notions of experience. Approach: To merge these areas, a review of literature identifies key approaches and missing links. This paper determines research gaps to propose a new holistic research agenda for sport services—specifically relevant to sport tourism. Findings/practical implications: This paper addresses types of sport experiences, economic dimensions of experiences, and business models to determine capabilities of delivering different types of experiences. These interrelated fields of analysis represent a platform for both academic and business stakeholders to shape the future of delivering sport tourism experiences–based on seeking a wider range of motivations in a specific spatial and activity context. Originality/value: A series of research questions and proposals are identified to support the need for future research. Extending understandings of experience in relation to consumer demand has the potential to result in practical elements of sought after experiences being incorporated into business models—aimed at delivering service value

Studies of Bs2∗(5840)0 and Bs1(5830)0 mesons including the observation of the Bs2∗(5840)0→B0KS0 decay in proton-proton collisions at s=8TeV.

Measurements of Bs2∗(5840)0 and Bs1(5830)0 mesons are performed using a data sample of proton-proton collisions corresponding to an integrated luminosity of , collected with the CMS detector at the LHC at a centre-of-mass energy of 8TeV . The analysis studies P-wave Bs0 meson decays into B(∗)+K- and B(∗)0KS0 , where the B+ and B0 mesons are identified using the decays B+→J/ψK+ and B0→J/ψK∗(892)0 . The masses of the P-wave Bs0 meson states are measured and the natural width of the Bs2∗(5840)0 state is determined. The first measurement of the mass difference between the charged and neutral B∗ mesons is also presented. The Bs2∗(5840)0 decay to B0KS0 is observed, together with a measurement of its branching fraction relative to the Bs2∗(5840)0→B+K- decay