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Social signs processing in a cognitive architecture for an humanoid robot

Procedia Computer Science 2018年 123卷 63-68页

作者： Agnese Augello Emanuele Cipolla Ignazio Infantino Adriano Manfré Giovanni Pilato Filippo Vella Institute for High Performance Computing and Networking National Research Council of Italy (ICAR-CNR) Palermo Italy

A social robot has to recognize human social intention in order to fully interact with him/her. People intention can be inferred by processing verbal and non-verbal communicative signs. In this work we describe an actions classification module embedded into a robot’s cognitive architecture, contributing to the interpretation of users behavior.

关键词： Cognitive Architecture Recurrent Neural Networks Actions Classification Pepper Robot

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Rapid Building of Software-based SDN Testbed using SDN Owl

Rapid Building of Software-based SDN Testbed using SDN Owl

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International Computer Science and Engineering Conference (ICSEC)

作者： Songpon Srisawai Putchong Uthayopas High Performance Computing and Networking Center Kasetsart University Bangkok Thailand

ISBN: (纸本)9781538681657;9781538681640

This paper presents the development of a software tool called SDN Owl that is used to facilitate a quick and easy construction of SDN testbed using open source software. SDN OWL is based on using a few computers, Linux operating system, Ansible, and OpenvSwitch to build an SDN testbed. The prototype testbed has been built using SDN OWL. The experimental results show that the SDN testbed that is built can function properly with a reasonable performance. In addition, the performance of hardware installation and container installation has been investigated as well. The result of this work enables an easy creation of a cost-effective SDN testbed from commodity computing components. This is very crucial for many small companies and research teams that want to study and develop the next generation SDN services and tools.

关键词： Containers Switches Software Hardware Buildings Monitoring

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Quantum Key Distribution over Complex Networks

arXiv

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arXiv 2025年

作者： Mariani, Luca Yehia, Raja Pascual-García, Carlos Centrone, Federico van der Kolk, Jasper Ángeles Serrano, M. Acín, Antonio ICAR CNR - Institute for High Performance Computing and Networking via Pietro Bucci Rende Italy University of Salerno Department of Physics "E. R. Caianiello" via Giovanni Paolo II 132 Fisciano Italy ICFO - Institut de Ciencies Fotoniques The Barcelona Institute of Science and Technology Castelldefels Spain Ciudad Universitaria Buenos Aires1428 Argentina BarcelonaE-08028 Spain Department of Condensed Matter Physics University of Barcelona Martí i Franquès 1 BarcelonaE-08028 Spain Department of Network and Data Science Central European University Vienna Vienna1100 Austria ICREA - Institució Catalana de Recerca i Estudis Avançats Barcelona08010 Spain

There exist several initiatives worldwide to deploy quantum key distribution (QKD) over existing fibre networks and achieve quantum-safe security at large scales. To understand the overall QKD network performance, it is required to transition from the analysis of individual links, as done so far, to the characterization of the network as a whole. In this work, we undertake this study by embedding QKD protocols on complex networks, which correctly model the existing fiber networks. We focus on networks with trusted nodes and on continuous-variable (CV) schemes, which have much higher key rates than their discrete-variable (DV) counterparts. In the effective CV network, however, many of the unique properties of complex networks, such as small-worldness and the presence of hubs, are lost due to the fast decay of the key rate with physical distance for CV systems. These properties can be restored when considering a hybrid network consisting of both CV and DV protocols, achieving at the same time high average rate and inter-connectivity. Our work opens the path to the study of QKD complex networks in existing infrastructures. Copyright © 2025, The Authors. All rights reserved.

关键词： Small-world networks

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Urban Intelligence: Toward the Digital Twin of Matera and Catania

Urban Intelligence: Toward the Digital Twin of Matera and Ca...

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Blockchain for Renewables Integration (BLORIN), Workshop on

作者： Giordana Castelli Amedeo Cesta Mario Ciampi Riccardo De Benedictis Giuseppe De Pietro Matteo Diez Giovanni Felici Roberto Malvezzi Barbara Masini Riccardo Pellegrini Andreas Scalas Giuseppe Stecca Lucanos Strambini Gabriella Tognola Paolo Ravazzani Emilio Fortunato Campana Engineering ICT and Technology for Energy and Transportation Dept. (DIITET) National Research Council (CNR) Rome Italy Institute of Cognitive Sciences and Technologies (ISTC) National Research Council (CNR) Rome Italy Institute for High Performance Computing and Networking (ICAR) National Research Council (CNR) Naples Italy Institute of Marine Engineering (INM) National Research Council (CNR) Rome Italy Institute for Systems Analysis and Computer Science (IASI) National Research Council (CNR) Rome Italy Engineering ICT and Technology for Energy and National Research Council (CNR) Rome Italy Institute of Electronics Computer and Telecommunication Engineering (IEIIT) National Research Council (CNR) Bologna Italy Institute for Applied Mathematics and Information Technologies (IMATI) National Research Council (CNR) Genoa Italy Institute for Systems Analysis and Computer Science “Antonio Ruberti” (IASI) National Research Council (CNR) Rome Italy Institute of Electronics Computer and Telecommunication Engineering (IEIIT) (CNR) Pisa Italy

ISBN: (纸本)9781665472500

The Urban Intelligence (UI) paradigm conceived by CNR consists of an ecosystem of digital technologies joined within a Digital Twin (DT) of the city aimed at improving the city governance towards goals addressed also by the UN Agenda 2030, such as urban environment, sustainability and resilience, wellbeing and quality of life, local development, and social inclusion. In particular, UI provides a set of candidate policies in complex scenarios, and supports policy makers and stakeholders in designing shared, evidence-based, and integrated solutions. UI is being applied for the first time to two Italian cities, Matera and Catania, paving the way for a deeper scientific framing of the paradigm, as well as for the technological development and testing of the core UI ecosystem in real-life situations. The paper introduces the UI key-concepts and components, illustrates the ongoing experimentations in these pilot cities related to the development of two DTs on parts of the urban areas, and presents some initial results.

关键词： Renewable energy sources Urban areas Ecosystems Lakes Digital twins Sensors Stakeholders

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Network performance Monitoring with Flexible Models of Multi-Point Passive Measurements 14

Network Performance Monitoring with Flexible Models of Multi...

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14th International Conference on Network and Service Management, CNSM 2018 and Workshops, 1st International Workshop on High-Precision Networks Operations and Control, HiPNet 2018 and 1st Workshop on Segment Routing and Service Function Chaining, SR+SFC 2018

作者： Perdices, Daniel Muelas, David Pedro, Luis De Vergara, Jorge E. Lopez De Dept. Electronics and Communication Technologies Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Naudit High Performance Computing and Networking S.L. Madrid Spain

ISBN: (纸本)9783903176140

Many management actions for networking infrastructures require to simultaneously consider the state of several network elements. This is particularly critical in the case of reconfigurable deployments, such as Virtual or Software-Defined Networks, to scale the affected equipment up and prevent performance bottlenecks. In this light, we present dPRISMA (distributed Passive Retrieval of Information, and Statistical Multipoint Analysis), a passive monitoring system intended to fit statistical models for network measurements and raise alarms in the case of extreme behaviors. As distinguishing features, dPRISMA relies on cost-effective multi-point network measurements, and is able to select a suitable parametric model optimizing the trade-off between fitting and complexity. Therefore, it can (i) correlate records collected from several vantage points and detect where performance issues are most likely to appear;(ii) adjust alarms in terms of the probability of events;and (iii) adapt its behavior to dynamic network conditions while presenting a fair identification of anomalous situations. We evaluate dPRISMA with experiments both in virtual environments and with real-world data to provide evidences of its applicability. © 2018 IFIP.

关键词： Virtual reality

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Question Classification by Convolutional Neural Networks Embodying Subword Information

Question Classification by Convolutional Neural Networks Emb...

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International Joint Conference on Neural Networks (IJCNN)

作者： Marco Pota Massimo Esposito Institute for High Performance Computing and Networking (ICAR) National Research Council of Italy (CNR) Naples Italy

Question Classification is a core module of Question Answering paradigm. Development of classification models based on neural networks showed that convolutional architectures allow obtaining uppermost results for this task. In particular, this type of approach avoids extracting features from questions, by treating text as a sequence of words, and transforming each word in a dense vector, named word embedding. Among different techniques to learn word embeddings, a recent approach takes into account also subword information, which could be very useful for morphologically rich languages. In this paper, a Question Classification approach based on word embedding using subword information and Convolutional Neural Networks is proposed, in order to improve classification accuracy. In particular, questions taken from a TRC dataset are considered, and a comparison between English and Italian languages is reported, by highlighting eventual improvements obtained by initializing word embeddings with advanced vectors learned in an unsupervised manner using skip- gram model and comprising character-based information.

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Exploring the Feasibility of Diegetic User Interfaces in Immersive Virtual Exhibitions within the Cultural Heritage

Exploring the Feasibility of Diegetic User Interfaces in Imm...

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International IEEE Conference on Signal-Image Technologies and Internet-Based System

作者： Giuseppe Caggianese Luigi Gallo Pietro Neroni Institute for High Performance Computing and Networking National Research Council of Italy (ICAR-CNR) Naples Italy

ISBN: (纸本)9781538693865;9781538693858

In the last few years, modern immersive technology has been used to exploit new digital resources overcoming the limitations of conventional exhibitions proving to be an invaluable instrument capable of bridging the gap between the visitor and the cultural space. However, to promote visitor enjoyment and to enhance the learning process in relation to the cultural heritage, it is fundamental to propose the cultural data to the visitor in an appropriate way through interfaces that help to focus the visitor's attention on the work of art in question. With this aim, new graphical user interfaces should be designed, following a diegetic approach and so providing a more natural and immersive environment to the user. Inspired by the gaming industry, in which the diegetic transformation of graphical user interfaces has already been introduced, in this paper, we will analyze the opportunities offered by the diegetic approach and will evaluate its relevance to the cultural domain. We will highlight the issues related to the applicability of diegetic user interfaces to an immersive virtual exhibition by discussing the different types of cultural data that can be proposed to a visitor and how that should be fictionally integrated into the scene.

关键词： Games Cultural differences Graphical user interfaces Three-dimensional displays Resists Art

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IoT-Centric Edge computing for Context-Aware Smart Environments

IoT-Centric Edge Computing for Context-Aware Smart Environme...

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IEEE International Congress on Internet of Things (ICIOT)

作者： Franco Cicirelli Antonio Guerrieri Alessandro Mercuri Giandomenico Spezzano Andrea Vinci CNR - National Research Council of Italy Institute for High Performance Computing and Networking (ICAR) Rende (CS) Italy

The ever increasing diffusion of the Internet of Things is currently promoting the development of pervasive Smart Environments. The effectiveness of such systems is highly related to the capability of dealing with possible changes in users' habits, adapting the system to people needs and envisaging people behaviors. For this purposes, it becomes important to have methodological approaches and technologies favoring the development of cognitive systems aware of what is happening inside them. In this paper a methodological approach for the development of context-aware IoT-based Smart Environments is proposed. Such approach relies on a three-layered architecture offering some well suited abstractions taking also into account that computational resources in a system can be located either at the edge of the network or in the Cloud. A case study is proposed which concerns the development of a Smart Office devoted to forecast workers' presence and to adapt the office environmental conditions to them.

关键词： Task analysis Edge computing Cloud computing Temperature sensors Temperature measurement Computer architecture

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Improving Influenza Forecasting with Web-Based Social Data

Improving Influenza Forecasting with Web-Based Social Data

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Carmela Comito Agostino Forestiero Clara Pizzuti National Research Council of Italy (CNR) Institute for High Performance Computing and Networking (ICAR) Rende CS Italy

ISBN: (纸本)9781538660522

Improving seasonal influenza forecasting combining official data sources with web search and social media is a recent research topic which can enhance situational awareness of healthcare organizations when monitoring the outbreak of seasonal flu. In this paper, a prediction model based on autoregression that combines data coming from official influenza surveillance system, with data from web search and social media regarding influenza is proposed. The model is evaluated on the two influenza seasons 2016-2017 and 2017-2018, restricted to Italy. The results show that by using Web-based social data, like Google search queries and tweets, we can obtain accurate weekly influenza predictions up to four weeks in advance. The proposed approach improves real-time influenza forecast compared to traditional surveillance systems based on data from sentinel doctors: the prediction error is reduced up to 47%, while the Pearson's correlation is improved of about 24%.

关键词： Google Twitter Predictive models Forecasting Market research Data models Surveillance

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Correction to: Clustering analysis of tumor metabolic networks

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BMC bioinformatics 2020年第1期21卷 494页

作者： Ichcha Manipur Ilaria Granata Lucia Maddalena Mario R Guarracino Institute for High-Performance Computing and Networking National Research Council Via P. Castellino 111 80131 Naples Italy. Institute for High-Performance Computing and Networking National Research Council Via P. Castellino 111 80131 Naples Italy. mario.guarracino@cnr.it. HSE - National Research University Higher School of Economics LATNA Laboratory 13 Rodionova Ulitsa Nizhny Novgorod Russia. mario.guarracino@cnr.it.

An amendment to this paper has been published and can be accessed via the original article.

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