Search results for "Object-oriented design"
showing 9 items of 39 documents
Multilayer Network Analysis: The Identification of Key Actors in a Sicilian Mafia Operation
2021
Recently, Social Network Analysis studies have led to an improvement and to a generalization of existing tools to networks with multiple subsystems and layers of connectivity. These kind of networks are usually called multilayer networks. Multilayer networks in which each layer shares at least one node with some other layer in the network are called multiplex networks. Being a multiplex network does not require all nodes to exist on every layer. In this paper, we built a criminal multiplex network which concerns an anti-mafia operation called “Montagna” and it is based on the examination of a pre-trial detention order issued on March 14, 2007 by the judge for preliminary investigations of t…
Using neural networks to obtain indirect information about the state variables in an alcoholic fermentation process
2020
This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg&ndash
Hierarchical Self-Assembly of Supramolecular Spintronic Modules into 1D- and 2D-Architectures with Emergence of Magnetic Properties
2004
Hierarchical self-assembly of complex supramolecular architectures allows for the emergence of novel properties at each level of complexity. The reaction of the ligand components A and B with Fe II cations generates the (2 K 2) grid-type functional building modules 1 and 2, presenting spin-tran- sition properties and preorganizing an array of coordination sites that sets the stage for a second assembly step. Indeed, binding of La III ions to 1 and of Ag I ions to 2 leads to a 1D columnar superstructure 3 and to a wall-like 2D layer 4, respectively, with concomitant modulation of the magnetic properties of 1 and 2. Thus, to each of the two levels of structural complexity generat- ed by the t…
Multi-Layer Offloading at the Edge for Vehicular Networks
2020
This paper proposes a multi-layer platform for job offloading in vehicular networks. Offloading is performed from vehicles in the Vehicular Domain towards Multi-Access Edge Computing (MEC) Servers deployed at the edge of the network, and between MEC Servers. Offloading decisions at both domains are challenging for the overall system performance. Optimization at the MEC Layer domain is obtained by model-based Reinforcement Learning, while a strategy to decide the best offloading rate from the Vehicular Domain is defined to achieve the desired trade-off between costs and performance. Numerical analysis shows the achieved performance.
$$PO^2$$ - A Process and Observation Ontology in Food Science. Application to Dairy Gels
2016
This paper focuses on the knowledge representation task for an interdisciplinary project called Delicious concerning the production and transformation processes in food science. The originality of this project is to combine data from different disciplines like food composition, food structure, sensorial perception and nutrition. Available data sets are described using different vocabularies and are stored in different formats. Therefore there is a need to define an ontology, called \(PO^2\) (Process and Observation Ontology), as a common and standardized vocabulary for this project. The scenario 6 of the NeON methodology was used for building \(PO^2\) and the core component is implemented i…
Convolutional Long Short-Term Memory Network for Multitemporal Cloud Detection Over Landmarks
2019
In this work, we propose to exploit both the temporal and spatial correlations in Earth observation satellite images through deep learning methods. In particular, the combination of a U-Net convolutional neural network together with a convolutional long short-term memory (LSTM) layer is proposed. This model is applied for cloud detection on MSG/SEVIRI image time series over selected landmarks. Implementation details are provided and our proposal is compared against a standard SVM and a U-Net without the convolutional LSTM layer but including temporal information too. Experimental results show that this combination of networks exploits both the spatial and temporal dependence and provides st…
Sub-symbolic Mapping of Cyc Microtheories in Data-Driven “Conceptual” Spaces
2007
The presented work aims to combine statistical and cognitive-oriented approaches with symbolic ones so that a conceptual similarity relationship layer can be added to a Cyc KB microtheory. Given a specific microtheory, a LSA-inspired conceptual space is inferred from a corpus of texts created using both ad hoc extracted pages from the Wikipedia repository and the built-in comments about the concepts of the specific Cyc microtheory. Each concept is projected in the conceptual space and the desired layer of subsymbolic relationships between concepts is created. This procedure can help a user in finding the concepts that are "sub-symbolically conceptually related" to a new concept that he want…
Hybridizing large neighborhood search and exact methods for generalized vehicle routing problems with time windows
2021
International audience; Delivery options are at the heart of the generalized vehicle routing problem with time windows (GVRPTW) allowing that customer requests are shipped to alternative delivery locations which can also have different time windows. Recently, the vehicle routing problem with delivery options was introduced into the scientific literature. It extends the GVRPTW by capacities of shared locations and by specifying service-level constraints defined by the customers' preferences for delivery options. The vehicle routing problem with delivery options also generalizes the vehicle routing problem with home roaming delivery locations and the vehicle routing problem with multiple time…
Towards enabling privacy preserving smart city apps
2016
Smart city applications are increasingly relying on personally identifiable data. A disclosure of such a data to a platform provider and possible 3rd parties represents a risk to the privacy of the application users. To mitigate the privacy risk, two-layer privacy-preserving platform architecture is introduced, wherein the personally identifiable information is dealt with at the inner layer (executed in a trusted environment), whereas only generic and personally unidentifiable information is made available to the apps at the outer layer of the architecture — e.g., in a form of app-specific events. The essential requirements for the platform are described, and the architectural implications …