Abstract
Internet of Things, IoT, is a promising methodology that has been increasing over the last years. It can be used to allow the connection and exchange data with other devices and systems over the Internet. One of the IoT connection protocols is the LoRaWAN, which has several advantages but has a low bandwidth and limited data transfer. There is a necessity of optimising the data transfer between devices. Some sensors have a 10 or 12 bits resolution, while LoRaWAN owns 8 bits or multiples slots of transmission remaining unused bits. This paper addresses a communication optimisation for wireless sensors resorting to encoding and decoding procedures. This approach is applied and validated on the real scenario of a wildfire detection system.

Abstract
The lack of general robotics purposed, accurate open source simulators is a major setback that limits the optimized trajectory generation research and general evolution of the robotics field. Spray painting is a particular case that has multiple advantages in using a simulator for exploring new algorithms, mainly the waste of materials and the dangers associated with a robotic manipulator. This paper demonstrates an implementation of spray painting on a previously existing simulator, SimTwo. Several metrics for optimization that evaluate the painted result are also proposed. In order to validate the implementation, we conducted a real world experiment that serves both as proof that the chosen spray distribution model translates to reality and as a way to calibrate the model parameters.

Abstract
A durable good monopolist faces a continuum of heterogeneous customers who make purchase decisions by comparing present and expected price-quality offers. The monopolist designs a sequence of price-quality menus to segment the market. We consider the Markov perfect equilibrium (MPE) of a game where the monopolist is unable to commit to future price-quality menus. We obtain the novel results that: (a) under certain conditions, the monopolist covers the whole market in the first period (even when a static Mussa-Rosen monopolist would not cover the whole market), because this is a strategic means to convince customers that lower prices would not be offered in future periods and that (b) this can happen only under the stage-wise Stackelberg leadership assumption (whereby consumers base their expectations on the value of the state variable at the end of the period). Conditions under which MPE necessarily involves sequentially trading are also derived.

Abstract

Abstract
The moisture transfer process in multilayered building components with an interface is very different than the moisture transfer considered when having different materials/layers separately. Quantifying moisture transfer in multi-layered systems through numerical simulations is essential to predict the real behaviour of those building materials in contact with moisture, which depends on the climatic conditions. Unfortunately, the contact phenomenon is neglected in numerical simulations which compromise the feasibility of the results. In this work, the moisture transfer in multi-layered building components is analysed in detail, for perfect contact and hydraulic contact interface. The “knee point” was detected, numerically, in water absorption curves and the moisture-dependent interface resistance was quantified and validated for transient conditions. The methodology proposed to detect the “knee point” can be also used in the future for different multilayer materials with an interface, in order to obtain more correct maximum hygric resistance values, to be used in future numerical simulations. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Abstract
Distribution warehouses are a critical part of supply chains, representing a nonnegligible share of the operating costs. This is especially true for unautomated, labor-intensive warehouses, partially due to time-consuming activities such as picking up items or traveling. Inventory categorization techniques, as well as zone storage assignment policies, may help in improving operations, but may also be short-sighted. This work presents a three-step methodology that uses probabilistic simulation, optimization, and event-based simulation (SOS) to analyze and experiment with layout and storage assignment policies to improve the picking performance. In the first stage, picking performance is estimated under different storage assignment policies and zone configurations using a probabilistic model. In the second stage, a mixed integer optimization model defines the overall warehouse layout by selecting the configuration and storage assignment policy for each zone. Finally, the optimized layout solution is tested under demand uncertainty in the third, final simulation phase, through a discrete-event simulation model. The SOS methodology was validated with three months of operational data from a large retailer's warehouse, successfully illustrating how it may be successfully used for improving the performance of a distribution warehouse.