Abstract Current mainstream approach to sensor data monitoring usually relies on cloud access: samples are acquired by connected devices and data processing is performed on remote servers. To improve responsiveness, security and resilience, devices and programming methodologies must be improved, with the aim of enabling data analytics at the edge. Unfortunately this is not an easy task, especially in the IoT... Current mainstream approach to sensor data monitoring usually relies on cloud access: samples are acquired by connected devices and data processing is performed on remote servers. To improve responsiveness, security and resilience, devices and programming methodologies must be improved, with the aim of enabling data analytics at the edge. Unfortunately this is not an easy task, especially in the IoT domain. In this paper, we present a research approach that manages at runtime the hardware/software configuration of a low-power processing system, with the aim of adapting to dynamically changing workloads optimizing power-relevant settings to the corresponding operating point. First, we present a first validation experiment, involving a hardware-software architecture for a connected sensor-processing node that allows the set of in-place processing tasks to be executed to be remotely controllable by an external user. The designed system is capable of dynamically adapting its operating point to the selected computational load, to minimize power consumption. The benefits of the proposed approach are tested on a use-case involving ECG monitoring, that, when selected, performs ECG classification using a lightweight convolutional neural network. Experimental results show how the proposed approach can provide more than 50% power consumption reduction for common ECG activity, with less than 2% memory footprint overhead and reconfiguring the system in less than 1 ms. Second we present our plans to extend this approach to more complex multi-core systems. Read More Read Less

Abstract Automated design and configuration of complex systems is well established as a research topic, specifically for constraint programming. In order to encode “quality of design” rules, i.e., preferences about the final outcomes, the encoding must be completed with optimization capabilities. Based on experience in the configuration of elevator systems we present a research agenda to develop methods and tools which should be able... Automated design and configuration of complex systems is well established as a research topic, specifically for constraint programming. In order to encode “quality of design” rules, i.e., preferences about the final outcomes, the encoding must be completed with optimization capabilities. Based on experience in the configuration of elevator systems we present a research agenda to develop methods and tools which should be able to leverage constraint solvers in order to compute designs for complex systems that can compete with the ones produced by humans. Besides elevator systems, we propose to evaluate the methodology and the tools on other case studies, e.g., hardware configuration or heating ventilation and air conditioning systems. Read More Read Less

Abstract The theme of causal attribution has generated a great deal of work and focuses on the factors to which people attribute their behavior. However, its use to explain the results of the evaluation and the support for the regulation of teaching and learning acts has rarely been raised. Indeed, in the evaluation act, which is a privileged moment for reframing the learning process, teachers... The theme of causal attribution has generated a great deal of work and focuses on the factors to which people attribute their behavior. However, its use to explain the results of the evaluation and the support for the regulation of teaching and learning acts has rarely been raised. Indeed, in the evaluation act, which is a privileged moment for reframing the learning process, teachers attribute the results obtained to the student himself, without worrying about the factors to which the student attribute itself these failures. This can distort the regulatory process and increase failure factors. The teacher’s attributions of failure often relate to the results of the evaluations and are often explained by factors external to him: such as the lack of commitment of the students, their incompetence and their degree of understanding. and these are internal factors for the student. The aim of this presentation is to show that: the regulation of the teaching and learning act should not only focus on the results of the evaluation but also on the factors to which the student himself attributes his own failure. Involving the student in the teaching act must also involve his involvement in the evaluation and regulation process. Read More Read Less