Global Propagation of Singularities for Time Dependent Hamilton-Jacobi Equations

We investigate the properties of the set of singularities of semiconcave solutions of Hamilton-Jacobi equations of the form \begin{equation*} u_t(t,x)+H(\nabla u(t,x))=0, \qquad\text{a.e. }(t,x)\in (0,+\infty)\times\Omega\subset\mathbb{R}^{n+1}\,. \end{equation*} It is well known that the singularities of such solutions propagate locally along generalized characteristics. Special generalized characteristics, satisfying an energy condition, can be constructed, under some assumptions on the structure of the Hamiltonian $H$. In this paper, we provide estimates of the dissipative behavior of the energy along such curves. As an application, we prove that the singularities of any viscosity solution of the above equation cannot vanish in a finite time

Analysis of the variability of cutting processes when many factors are perturbed.

Since the knowledge of industrial processes is mainly based on virtualisation, it is fundamental to develop a better understanding of the real processes performing analysis from an industrial point of view. Every analysis must use tools and solutions that could be really useful for industries, and become improvement keys for success. This paper shows a structured analysis of a turning process, to gain useful information, to evaluate experimental data and to define some improvement guidelines. On the basis of an excellent dataset, the main objective is to perform statistical analyses to estimate the influence of critical factors on response variables

Learner models in online personalized educational experiences: an infrastructure and some experim

Technologies are changing the world around us, and education is not immune from its influence: the field of teaching and learning supported by the use of Information and Communication Technologies (ICTs), also known as Technology Enhanced Learning (TEL), has witnessed a huge expansion in recent years. This wide adoption happened thanks to the massive diffusion of broadband connections and to the pervasive needs for education, highly connected to the evolution in sciences and technologies. Therefore, it has pushed up the usage of online education (distance and blended methodologies for educational experiences) to, even in lately years, unexpected rates. Alongside with the well known potentialities, digital-based educational tools come with a number of downsides, such as possible disengagement on the part of the learner, absence of the social pressures that normally exist in a classroom environment, difficulty or even inability from the learners to self-regulate and, last but not least, depletion of the stimulus to actively participate and cooperate with lectures and peers. These difficulties impact the teaching process and the outcomes of the educational experience (i.e. learning process), being a serious limit and questioning the broader applicability of TEL solutions. To overcome these issues, there is a need of tools to support the learning process. In the literature, one of the known approach to improve the situation is to rely on a user profile, that collects data during the use of the eLearning platforms or tool. The created profile can be used to adapt the behaviour and the contents proposed to the learner. On top of this model, some researches stressed the positive effects stimulated by the disclosure of the model itself for inspection purposes by the learner. This disclosed model is known as Open Learner Model (OLM). The idea of opening learners' profile and eventually integrate them with external on-line resources is not new and it has the ultimate goal of creating global and long-run indicators of the learner's profile. Also the representation aspect of the learner model plays a role, moving from the more traditional approach based on the textual and analytic/extensive representation to the graphical indicators that are able to summarise and to present one or more of the model characteristics in a way that is considered more effective and natural for the user consumption. Relying on the same learner models, and stressing the different aggregation and representation capabilities, it is possible to either support self-reflection of the learner or to foster the tutoring process to allow proper supervision by the tutor/teacher. Both the objectives can be reached through the graphical representation of the relevant information, presented in different ways. Furthermore, with such an open approach for the learner model, the concepts of personalisation and adaptation acquire a central role in the TEL experience, overcoming the previous limits related to the impossibility to observe and explain to the learner the reasons for such an intervention from the tool itself. As a consequence, the introduction of different tools, platforms, widgets and devices in the learning process, together with the adaptation process based on the learner profiles, can create a personal space for a potential fruitful usage of the rich and widespread amount of resources available to the learner. This work aimed at analysing the way a learner model could be represented in visual presentation to the system users, exploring the effects and performances for learners and teachers. Subsequently, it concentrated in investigating how the adoption of adaptive and social visualisations of OLM could affect the student experience within a TEL context. The motivation was twofold. On one side was to show that the approach of mixing data from heterogeneous and not already related data sources could have a meaningful didactic interpretations, whether on the other one was to measure the perceived impact of the introduction on online experiences of the adaptivity (and of social aspects) in the graphical visualisations produced by such a tool. In order to achieve these objectives, the present work analysed and addressed them through an approach that merged user data in learning platforms, implementing a learner profile. This was accomplished by means of the creation of a tool, named GVIS, to elaborate on the collected user actions in platforms enabling remote teaching. A number of test cases were performed and analysed, adopting the developed tool as the provider to extract, to aggregate and to represent the data for the learners' model. The GVIS tool impact was then estimated with self- evaluation questionnaires, with the analysis of log files and with knowledge quiz results. Dimensions such as the perceived usefulness, the impact on motivation and commitment, the cognitive overload generated, and the impact of social data disclosure were taken into account. The main result found by the application of the developed tool in TEL experiences was to have an impact on the behaviour of online learners when used to provide them with indicators around their activities, especially when enhanced with social capabilities. The effects appear to be amplifies in those cases where the widget usage is as simplified as possible. From the learner side, the results suggested that the learners seem to appreciate the tool and recognise its value. For them the introduction as part of the online learning experience could act as a positive pressure factor, enhanced by the peer comparison functionality. This functionality could also be used to reinforce the student engagement and positive commitment to the educational experience, by transmitting a sense of community and stimulating healthy competition between learners. From the teacher/tutor side, they seemed to be better supported by the presentation of compact, intuitive and just-in-time information (i.e. actions that have an educational interpretation or impact) about the monitored user or group. This gave them a clearer picture of how the class is currently performing and enabled them to address performance issues by adapting the resources and the teaching (and learning) approach accordingly. Although a drawback was identified regarding the cognitive overload, the data collected showed that users generally considered this kind of support useful. There is also indications that further analyses can be interesting to explore the effects introduced in the teaching practices by the availability and usage of such a tool

Techno-Economic Optimization Of A Stand-Alone Hybrid Microgrid For The Rural Electrification In Sub Saharan Africa

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.This paper is focused on the design of a stand-alone micro-grid for rural electrification. The aim of this work is to define the best mix of energy sources and the optimal size of the energy storage for a small isolated village on the Ghana seaside. We obtain the optimal solution by simulating one year of operation for several different combinations of prime movers and battery sizes and comparing the economic performance in terms of levelized cost of electricity. We adopt a rolling-horizon strategy to simulate the micro-grid operation, which optimizes generators and loads schedule over a 12 hours time horizon. We solve a Mixed Integer Linear Programming problem for each time step, exploiting weather forecast for predicting the energy available from sun and wind and taking into account a realistic operation of each component like energy losses and costs during start-up of dispatchable generators and ageing cost for the battery. The optimal configuration found includes a 30 kWel wind turbine, a 60 kWel photovoltaic array, a 30 kWel biomass fired ORC and a 50 kWel diesel. The limited use of the diesel engine in the optimal solution demonstrates that energy access in a sustainable and economic way is possible even in rural contexts. Finally, two sensitivity analyses are presented varying the cost of the biomass and the error of wind speed forecast.cf201

Keyword Based Keyframe Extraction in Online Video Collections

Keyframe extraction methods aim to find in a video sequence the most significant frames, according to specific criteria. In this paper we propose a new method to search, in a video database, for frames that are related to a given keyword, and to extract the best ones, according to a proposed quality factor. We first exploit a speech to text algorithm to extract automatic captions from all the video in a specific domain database. Then we select only those sequences (clips), whose captions include a given keyword, thus discarding a lot of information that is useless for our purposes. Each retrieved clip is then divided into shots, using a video segmentation method, that is based on the SURF descriptors and keypoints. The sentence of the caption is projected onto the segmented clip, and we select the shot that includes the input keyword. The selected shot is further inspected to find good quality and stable parts, and the frame which maximizes a quality metric is selected as the best and the most significant frame. We compare the proposed algorithm with another keyframe extraction method based on local features, in terms of Significance and Quality

Activity Monitoring Made Easier by Smart 360-degree Cameras

This paper proposes the use of smart 360-degree cameras for activity monitoring. By exploiting the geometric properties of these cameras and adopting off-the-shelf tracking algorithms adapted to equirectangular images, this paper shows how simple it becomes deploying a camera network, and detecting the presence of pedestrians in predefined regions of interest with minimal information on the camera, namely its height. The paper further shows that smart 360-degree cameras can enhance motion understanding in the environment and proposes a simple method to estimate the heatmap of the scene to highlight regions where pedestrians are more often present. Quantitative and qualitative results demonstrate the effectiveness of the proposed approach

Automating the simulation of SME processes through a discrete event parametric model

At the factory level, the manufacturing system can be described as a group of processes governed by complex weaves of engineering strategies and technologies. Decision- making processes involve a lot of information, driven by managerial strategies, technological implications and layout constraints. Many factors affect decisions, and their combination must be carefully managed to determine the best solutions to optimize performances. In this way, advanced simulation tools could support the decisional process of many SMEs. The accessibility of these tools is limited by knowledge, cost, data availability and development time. These tools should be used to support strategic decisions rather than specific situations. In this paper, a novel approach is proposed that aims to facilitate the simulation of manufacturing processes by fast modelling and evaluation. The idea is to realize a model that is able to be automatically adapted to the user’s specific needs. The model must be characterized by a high degree of flexibility, configurability and adaptability in order to automatically simulate multiple/heterogeneous industrial scenarios. In this way, even a SME can easily access a complex tool, perform thorough analyses and be supported in taking strategic decisions. The parametric DES model is part of a greater software platform developed during COPERNICO EU funded project