Search results for "NETWORK"
showing 10 items of 7718 documents
Geography versus topology in the European Ownership Network
2011
In this paper, we investigate the network of ownership relationships among European firms and its embedding in the geographical space. We carry out a detailed analysis of geographical distances between pairs of nodes, connected by edges or by shortest paths of varying length. In particular, we study the relation between geographical distance and network distance in comparison with a random spatial network model. While the distribution of geographical distance can be fairly well reproduced, important deviations appear in the network distance and in the size of the largest strongly connected component. Our results show that geographical factors allow us to capture several features of the netw…
Systematic comparison of Artificial Neural Networks for a SHM procedure applied to Composite Structure
2014
The problems related to damage detection represents a primary concern, particularly in the framework of composite structure. In fact, for this kind of structures barely visible damage can occur. Moreover, one of the major in-service damage of composite aircraft strcutures is represented by disbonds between the stiffeners and the skin undergoing dynamic or post-buckling loads. The effective implementation of a SHM system relies on the synthesis of non-destructive technique (NDT), fracture mechanics, sensors technology, data manipulation and signal processing, and it can receive a great improvement through the use of an Artificial Neural Networks. Different architectures of Artificial Neural …
A convolutional neural network for virtual screening of molecular fingerprints
2019
In the last few years, Deep Learning (DL) gained more and more impact on drug design because it allows a huge increase of the prediction accuracy in many stages of such a complex process. In this paper a Virtual Screening (VS) procedure based on Convolutional Neural Networks (CNN) is presented, that is aimed at classifying a set of candidate compounds as regards their biological activity on a particular target protein. The model has been trained on a dataset of active/inactive compounds with respect to the Cyclin-Dependent Kinase 1 (CDK1) a very important protein family, which is heavily involved in regulating the cell cycle. One qualifying point of the proposed approach is the use of molec…
Are Neural Networks Imitations of Mind?
2015
Artificial neural networks are often understood as a good way to imitate mind through the web structure of neurons in brain, but the very high complexity of human brain prevents to consider neural networks as good models for human mind;anyway neural networks are good devices for computation in parallel. The difference between feed-forward and feedback neural networks is introduced; the Hopfield network and the multi-layers Perceptron are discussed. In a very weak isomorphism (not similitude) between brain and neural networks, an artificial form of short term memory and of acknowledgement, in Elman neural networks, is proposed.
Value Creation and Power Asymmetries in Digital Ecosystems : A Study of a Cloud Gaming Provider
2020
Digital platforms connecting users and service providers have a central role in determining the value creation structure of ecosystems. Platform developers try to achieve a dominant position for the platform with a strong ecosystem around it. The size and attractiveness of the services can attract new users, and growing user volume can bring new co-operative service providers to the service partner network. An interesting question is how the presence of power and potential power asymmetry affect the value creation capability and the structure of a network around a platform? This chapter describes an example of value creation and the influence of power asymmetry in a digital ecosystem built …
Interactive Effects of Explicit Emergent Structure: A Major Challenge for Cognitive Computational Modeling
2015
International audience; David Marr's (1982) three-level analysis of computational cognition argues for three distinct levels of cognitive information processingnamely, the computational, representational, and implementational levels. But Marr's levels areand were meant to bedescriptive, rather than interactive and dynamic. For this reason, we suggest that, had Marr been writing today, he might well have gone even farther in his analysis, including the emergence of structurein particular, explicit structure at the conceptual levelfrom lower levels, and the effect of explicit emergent structures on the level (or levels) that gave rise to them. The message is that today's cognitive scientists …
Complex Detection in Protein-Protein Interaction Networks: A Compact Overview for Researchers and Practitioners
2012
The availability of large volumes of protein-protein interaction data has allowed the study of biological networks to unveil the complex structure and organization in the cell. It has been recognized by biologists that proteins interacting with each other often participate in the same biological processes, and that protein modules may be often associated with specific biological functions. Thus the detection of protein complexes is an important research problem in systems biology. In this review, recent graph-based approaches to clustering protein interaction networks are described and classified with respect to common peculiarities. The goal is that of providing a useful guide and referenc…
A probabilistic expert system for predicting the risk of Legionella in evaporative installations
2011
Research highlights? The bacterium Legionella usually lives in water sources such as cooling towers. ? We discuss a probabilistic expert system for predicting the risk of Legionella. ? The expert system has a master-slave architecture. ? The inference engine is implemented through Bayesian reasoning. ? Bayesian networks model and connect relationships for chemical and physical variables. Early detection in water evaporative installations is one of the keys to fighting against the bacterium Legionella, the main cause of Legionnaire's disease. This paper discusses the general structure, elements and operation of a probabilistic expert system capable of predicting the risk of Legionella in rea…
The Insect Mushroom Bodies: a Paradigm of Neural Reuse
2013
This paper is devoted to discuss the implementation of models,which are inspired by the fly Drosophila melanogaster and able to handle open problems in the field of robotics such as attention, expectation and sequence learning. The role of the Mushroom Bodies (MBs) in solving these tasks is analyzed in detail and a unifying plausible biologically inspired model is proposed. The developed neural structure is able to show different capabilities in line with the paradigm of neural reuse. The same neural circuit can be exploited to accomplish multiple tasks showing interesting capabilities such as attention, expectation and delayed match-to-sample. The simulation results here reported suggest a…
The impact of user’s availability on On-line Ego Networks: a Facebook analysis
2016
We have defined and implemented a Facebook application to log a Facebook dataset.We have studied and validated the structural properties of the whole dataset and of the Dunbar ego networks.We have analyzed the interactions of the users.The availability of the users in the Dunbar ego networks have been investigated.Our results reveal the presence of the temporal homophily property in the Dunbar ego networks. Online Social Networks (OSNs) are the most popular applications in todays Internet and they have changed the way people interact with each other. Understanding the structural properties of OSNs and, in particular, how users behave when they connect to OSNs is crucial for designing user-c…