Abstract
If we want robots to engage effectively with humans in service applications or in collaborative work scenarios they have be endowed with the capacity to perceive the passage of time and control the timing of their actions. Here we report result of a robotics experiment in which we test a computational model of action timing based on processing principles of neurodynamics. A key assumption is that elapsed time is encoded in the consistent buildup of persistent population activity representing the memory of sensory or motor events. The stored information can be recalled using a ramp-to-threshold dynamics to guide actions in time. For the experiment we adopt an assembly paradigm from our previous work on natural human-robot interactions. The robot first watches a human executing a sequence of assembly steps. Subsequently, it has to execute the steps from memory in the correct order and in synchrony with an external timing signal. We show that the robot is able to efficiently adapt its motor timing and to store this information in memory using the temporal mismatch between the neural processing of the sensory feedback about executed actions and the external cue. © 2017 IEEE.

Abstract
Distributed and heterogeneous systems (DHS), running over interconnected mobile and cloud-based platforms, are used in a growing number of domains for provisioning end-to-end services to users. Testing DHS is particularly important and challenging, with little support being provided by current tools. In order to assess the current state of the practice regarding the testing of DHS and identify opportunities and priorities for research and innovation initiatives, we conducted an exploratory survey that was responded by 147 software testing professionals that attended industry-oriented software testing conferences. The survey allowed us to assess the relevance of DHS in software testing practice, the most important features to be tested in DHS, the current status of test automation and tool sourcing for testing DHS, and the most desired features in test automation solutions for DHS. Some follow up interviews allowed us to further investigate drivers and barriers for DHS test automation. We expect that the results presented in the paper are of interest to researchers, tool vendors and service providers in this field.

Abstract
The use of rigid robot manipulators with good performance in industrial applications demands a proper robust and optimized control technique. Several works have proven the efficient use of metaheuristics optimization algorithms to work with complex problems in the robotic area. In this work, it is proposed the use of Grey Wolf Optimizer (GWO) with chaotic basis to optimize the parameters of a robust Higher Order Sliding Modes (HOSM) controller for the position control in joint space of a rigid robot manipulator. A total of seven test cases were considered varying the chosen chaotic map, face to the original GWO and the general repeatability of such algorithm is improved using chaotic versions. Also, two cost functions were tested within the HOSM optimization. Simulation results suggest that both algorithm and cost function formulations influence the chaotic map choice. In fact, the chattering problem, presented by HOSM controllers, is reduced when the cost function attempts to minimize the total variation of the control signal.

Abstract
Sugarcane cultivation is important for the economy of many countries, particularly for Brazil. This plant has been used to produce sugar, ethanol, second generation ethanol, fertilizers, as well as bioelectricity. Due to production growth and the establishment of mechanized sugarcane harvesting, this process needs to be optimized. High costs are linked to mechanized harvesting, which affect the total cost of production. One of the costs of harvesting is related to the long time the sugarcane harvesting machine takes to change the crop row to be cut. To help reduce costs, this work proposes a mathematical model to the Route Planning Problem for Mechanized Harvesting. This mathematical model minimizes the time of maneuvering the harvesting machine and, consequently, reduces fuel and labor costs, among others. Computer tests were performed using data supplied by a company from the sugarcane energy sector located in the state of São Paulo, Brazil. The results were compared to the traditional routes used by the company and proved the efficiency of the mathematical model in supplying solutions that minimize the time of harvesting machine maneuvers. Not only are there economic benefits, but also environmental ones that can be obtained.

Abstract
This letter is an enhancement to our previous paper that quantifies additional reinforcement costs (ARCs) for low-voltage assets under moderate degree of three-phase imbalance. The original formulas cause an overestimation of the ARCs under severe imbalance. This letter first quantifies the threshold of the severe degree of imbalance (DIB), below which the original formulas are applicable. Then, the ARC formulas are extended to account for the whole range of DIB. Case studies demonstrate that when the asset loading level is below 33.3% (50%) for a feeder (a transformer), the DIB never exceeds the threshold and the original ARC formulas are applicable; otherwise, the DIB can exceed the threshold and the extended formulas yield correct ARCs.

Abstract
This paper presents an overview of the work under development within MAESTRI EU-funded collaborative project. The MAESTRI Total Efficiency Framework (MTEF) aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: (a) an effective management system targeted at process continuous improvement; (b) Efficiency assessment tools to support improvements, optimisation strategies and decision support; (c) Industrial Symbiosis paradigm to gain value from waste and energy exchange; (d) an Internet-of-Things infrastructure to support easy integration and data exchange among shop-floor, business systems and tools.