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On Integrating Social and Sensor Networks for Emergency Management
No full textThe 2010 earthquake in Haiti is often referred to as the turning point that changed the way social media can be used during disasters. The development of strategies, technologies and tools to enhance user collaboration around disasters has become an emergent field, and their integration with appropriate sensor networks presents itself as an effective solution to drive decision making in emergency management.
In this paper, we present a review of existing disaster management systems and their underlying strategies and technologies, and identify the limitations of the tools in which they are implemented. We then propose an architecture for disaster management that integrates the mining of social networks and the use of sensor networks as two complementary technologies to overcome the limitations of the current emergency management tools
A Proactive Approach for Runtime Self-adaptation Based on Queueing Network Fluid Analysis
No full textComplex software systems are required to adapt dynamically to changing workloads and scenarios, while guaranteeing a set of performance objectives. This is not a trivial task, since run-time variability makes the process of devising the needed resources challenging for software designers. In this context, self-adaptation is a promising technique that work towards the specification of the most suitable system configuration, such that the system behavior is preserved while meeting performance requirements. In this paper we propose a proactive approach based on queuing networks that allows self-adaptation by predicting performance flaws and devising the most suitable system resources allocation. The queueing network model represents the system behavior and embeds the input parameters (e.g., workload) observed at run-time. We rely on fluid approximation to speed up the analysis of transient dynamics for performance indices. To support our approach we developed a tool that automatically generates simulation and fluid analysis code from an high-level description of the queueing network. An illustrative example is provided to demonstrate the effectiveness of our approach
Perspectives on optimal control of Varicella and Herpes Zoster by mass routine varicella vaccination: the effects of Immunity Boosting
No full textThe eNanoMapper database for nanomaterial safety information
No full textBackground: The NanoSafety Cluster, a cluster of projects funded by the European Commision, identified the need for a computational infrastructure for toxicological data management of engineered nanomaterials (ENMs). Ontologies, open standards, and interoperable designs were envisioned to empower a harmonized approach to European research in nanotechnology. This setting provides a number of opportunities and challenges in the representation of nanomaterials data and the integration of ENM information originating from diverse systems. Within this cluster, eNanoMapper works towards supporting the collaborative safety assessment for ENMs by creating a modular and extensible infrastructure for data sharing, data analysis, and building computational toxicology models for ENMs.
Results: The eNanoMapper database solution builds on the previous experience of the consortium partners in supporting diverse data through flexible data storage, open source components and web services. We have recently described the design of the eNanoMapper prototype database along with a summary of challenges in the representation of ENM data and an extensive review of existing nano-related data models, databases, and nanomaterials-related entries in chemical and toxicogenomic databases. This paper continues with a focus on the database functionality exposed through its application programming interface (API), and its use in visualisation and modelling. Considering the preferred community practice of using spreadsheet templates, we developed a configurable spreadsheet parser facilitating user friendly data preparation and data upload. We further present a web application able to retrieve the experimental data via the API and analyze it with multiple data preprocessing and machine learning algorithms.
Conclusion: We demonstrate how the eNanoMapper database is used to import and publish online ENM and assay data from several data sources, how the “representational state transfer” (REST) API enables building user friendly interfaces and graphical summaries of the data, and how these resources facilitate the modelling of reproducible quantitative structure–activity relationships for nanomaterials (NanoQSAR)
Il Futuro della Cyber Security in Italia. Un libro bianco per raccontare le principali sfide che il nostro Paese dovrà affrontare nei prossimi cinque anni
No full textDetection and density estimation of goblet cells in confocal endoscopy for the evaluation of celiac disease
No full textCeliac Disease (CD) is an immune-mediated enteropathy, diagnosed in the clinical practice by intestinal biopsy and the concomitant presence of a positive celiac serology. Confocal Laser Endomicroscopy (CLE) allows skilled and trained experts to potentially perform in vivo virtual histology of small-bowel mucosa. In particular, it allows the qualitative evaluation of mucosa alteration such as a decrease in goblet cells density, presence of villous atrophy or crypt hypertrophy. We present a semi-automatic computer-based method for the detection of goblet cells from confocal endoscopy images, whose density changes in case of pathological tissue. After a manual selection of a suitable region of interest, the candidate columnar and goblet cells' centers are first detected and the cellular architecture is estimated from their position using a Voronoi diagram. The region within each Voronoi cell is then analyzed and classified as goblet cell or other. The results suggest that our method is able to detect and label goblet cells immersed in a columnar epithelium in a fast, reliable and automatic way. Accepting 0.44 false positives per image, we obtain a sensitivity value of 90.3. Furthermore, estimated and real goblet cell densities are comparable (error: 9.7 ± 16.9, correlation: 87.2, R2 = 76)
Nonlinear fracture dynamics of laminates with finite thickness adhesives
No full textFinite thickness interfaces, such as structural adhesives, are often simplified from the modeling point of view by introducing ideal cohesive zone models that do not take into account the finite thickness properties in the evaluation of the interface stiffness and inertia. In the present work, the nonlinear dynamic response of those layered systems is numerically investigated according to the finite element method. The weak form of the dynamic equilibrium is written by including not only the contribution of cohesive interfaces related to the virtual work exerted by the cohesive tractions for the corresponding relative displacements, but also considering the work done by the dynamic forces of the finite thickness interfaces resulting from their inertia properties. A fully implicit solution scheme both in space and in time is exploited and the numerical results for the double cantilever beam test show that the role of finite thickness properties is not negligible as far as the crack growth kinetics and the dynamic strength increase factor are concerned
Model Predictive Control for Linear Impulsive Systems
No full textLinear impulsive control systems have been extensively studied with respect to their equilibrium points which, in most cases, are no other than the origin. However, the trajectory of an impulsive system cannot be stabilized to arbitrary desired points hindering their utilization in a great many applications. In this paper, we study the equilibrium of linear impulsive systems with respect to target-sets. We properly extend the notion of invariance and design stabilizing model predictive controllers (MPC). Finally, we apply the proposed methodology to control the intravenous bolus administration of Lithium