Multiresolution Techniques for Real–Time Visualization of Urban Environments and Terrains

In recent times we are witnessing a steep increase in the availability of data coming from real–life environments. Nowadays, virtually everyone connected to the Internet may have instant access to a tremendous amount of data coming from satellite elevation maps, airborne time-of-flight scanners and digital cameras, street–level photographs and even cadastral maps. As for other, more traditional types of media such as pictures and videos, users of digital exploration softwares expect commodity hardware to exhibit good performance for interactive purposes, regardless of the dataset size. In this thesis we propose novel solutions to the problem of rendering large terrain and urban models on commodity platforms, both for local and remote exploration. Our solutions build on the concept of multiresolution representation, where alternative representations of the same data with different accuracy are used to selectively distribute the computational power, and consequently the visual accuracy, where it is more needed on the base of the user’s point of view. In particular, we will introduce an efficient multiresolution data compression technique for planar and spherical surfaces applied to terrain datasets which is able to handle huge amount of information at a planetary scale. We will also describe a novel data structure for compact storage and rendering of urban entities such as buildings to allow real–time exploration of cityscapes from a remote online repository. Moreover, we will show how recent technologies can be exploited to transparently integrate virtual exploration and general computer graphics techniques with web applications

a novel approach to achieve breast symmetry in a single stage procedure

Preservation of the skin envelope and the inframammary fold is the main factor in achieving breast symmetry in unilateral reconstruction. Skin sparing mastectomy (SSM) type-IV followed by immediate autologous reconstruction and contralateral symmetrization permits realizing this goal in large, ptotic breasted patients, and tumor superficially located in the inferior quadrants. If the tumor is superficially located in the superior or inferior quadrants with a previous lumpectomy or quadrantectomy scar in the superior quadrants, modified radical mastectomy and a staged procedure are recommended to avoid poor cosmetic results. Two patients who underwent immediate autologous reconstruction following SSM type-V with contralateral symmetrization in a one-stage procedure are presented

Towards Self-evolving Context-aware Services

The introduction of new communication infrastructures such as Beyond 3rd Generation (B3G) and the widespread usage of small computing devices are rapidly changing the way we use and interact with technology to perform everyday tasks. Ubiquitous networking empowered by B3G networking makes it possible for mobile users to access networked software services across continuously changing heterogeneous infrastructures by resource-constrained devices. Heterogeneity and devices' limitedness, create serious problems for the development and dynamic deployment of mobile applications that are able to run properly on the execution context and consume services matching with the users' expectations. Furthermore, the everchanging B3G environment calls for applications that self-evolve according to context changes. Out of these problems, self-evolving adaptable applications are increasingly emerging in the software community. In this paper we describe how CHAMELEON, a declarative framework for tailoring adaptable applications, is being used for tackling adaptation and self-evolution within the IST PLASTIC project

Coverage and Deployment Analysis of Narrowband Internet of Things in the Wild

Narrowband Internet of Things (NB-IoT) is gaining momentum as a promising technology for massive Machine Type Communication (mMTC). Given that its deployment is rapidly progressing worldwide, measurement campaigns and performance analyses are needed to better understand the system and move toward its enhancement. With this aim, this paper presents a large scale measurement campaign and empirical analysis of NB-IoT on operational networks, and discloses valuable insights in terms of deployment strategies and radio coverage performance. The reported results also serve as examples showing the potential usage of the collected dataset, which we make open-source along with a lightweight data visualization platform.Comment: Accepted for publication in IEEE Communications Magazine (Internet of Things and Sensor Networks Series

String Stability of a Vehicular Platoon with the use of Macroscopic Information

We investigate the possibility to use macroscopic information to improve control performance of a vehicular platoon composed of autonomous vehicles. A general mesoscopic traffic modeling is described, and a closed loop String Stability analysis is performed using Input-to-State Stability (ISS) results. Examples of mesoscopic control laws are provided and shown to ensure String Stability properties. Simulations are implementedin order to validate the control laws and to show the efficacy of the proposed approach.Comment: arXiv admin note: substantial text overlap with arXiv:2003.1252

Informed classification of sweeteners/bitterants compounds via explainable machine learning

Perception of taste is an emergent phenomenon arising from complex molecular interactions between chemical compounds and specific taste receptors. Among all the taste perceptions, the dichotomy of sweet and bitter tastes has been the subject of several machine learning studies for classification purposes. While previous studies have provided accurate sweeteners/bitterants classifiers, there is ample scope to enhance these models by enriching the understanding of the molecular basis of bitter-sweet tastes. Towards these goals, our study focuses on the development and testing of several machine learning strategies coupled with the novel SHapley Additive exPlanations (SHAP) for a rational sweetness/bitterness classification. This allows the identification of the chemical descriptors of interest by allowing a more informed approach toward the rational design and screening of sweeteners/bitterants. To support future research in this field, we make all datasets and machine learning models publicly available and present an easy-to-use code for bitter-sweet taste prediction