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3rd International Workshop on Visualization and Interaction for Ontologies and Linked Data, VOILA 2017

作者： Graziosi, Alice Di Iorio, Angelo Poggi, Francesco Peroni, Silvio DASPLab - Digital and Semantic Publishing Laboratory DISI - Department of Computer Science and Engineering University of Bologna Italy

This paper aims to tackle on Linked Open Data (LOD) customised visualisations. The work is part of an ongoing research on interfaces and tools for helping non-programmers to easily present, analyse and support sense making over large semantic dataset. The customisation is a key aspect of our work. Producing effective customised visualisations is still difficult due to the complexity of the existing tools and the limited set of options they offer, especially to those with little knowledge in LOD and semantic data models. How can we give users full control on the primitives of the visualisation and their properties, without requiring them to master Semantic Web technologies or programming languages? The paper presents a conceptual model that can be used as a reference to build tools for generating customisable infoviews. We used it to conduct a survey on existing tools in terms of customisation capabilities. Starting from the feedback collected in this phase, we will implement these customisation features into some prototypes we are currently experimenting on.

关键词： Visualization

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Argumentative Link Prediction using Residual Networks and Multi-Objective Learning 5

Argumentative Link Prediction using Residual Networks and Mu...

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5th Workshop on Argument Mining, co-located with EMNLP 2018

作者： Galassi, Andrea Lippi, Marco Torroni, Paolo Department of Computer Science and Engineering DISI University of Bologna Italy Department of Sciences and Methods for Engineering University of Modena Reggio Emilia Italy

ISBN: (纸本)9781948087698

We explore the use of residual networks for argumentation mining, with an emphasis on link prediction. The method we propose makes no assumptions on document or argument structure. We evaluate it on a challenging dataset consisting of user-generated comments collected from an online platform. Results show that our model outperforms an equivalent deep network and offers results comparable with state-of-the-art methods that rely on domain knowledge. © 2018 Association for Computational Linguistics.

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A master-slave synchronization model for enhanced servo clock design

A master-slave synchronization model for enhanced servo cloc...

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IEEE International Symposium on Precision Clock Synchronization for Measurement, Control and Communication, ISPCS '09

作者： Macii, D. Fontanelli, D. Petri, D. DISI - Department of Information Engineering and Computer Science University of Trento Via Sommarive 14 38100 Trento Italy

ISBN: (纸本)9781424443925

Slave servo clocks have an essential role in hardware and software synchronization techniques based on Precision Time Protocol (PTP). The objective of servo clocks is to remove the drift between slave and master nodes, while keeping the output timing jitter within given uncertainty boundaries. Up to now, no univocal criteria exist for servo clock design. In fact, the relationship between controller design, performances and uncertainty sources is quite evanescent. In this paper, we propose a quite simple, but exhaustive linear model, which is expected to be used in the design of enhanced servo clock architectures. ©2009 IEEE.

关键词： Synchronization

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Learning interpretable and statistically significant knowledge from unlabeled corpora of social text messages: A novel methodology of descriptive text mining 9

Learning interpretable and statistically significant knowled...

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9th International Conference on Data science, Technology and Applications, DATA 2020

作者： Frisoni, Giacomo Moro, Gianluca Carbonaro, Antonella Department of Computer Science and Engineering – DISI University of Bologna Via dellUniversità 50 CesenaI-47522 Italy

ISBN: (纸本)9789897584404

Though the strong evolution of knowledge learning models has characterized the last few years, the explanation of a phenomenon from text documents, called descriptive text mining, is still a difficult and poorly addressed problem. The need to work with unlabeled data, explainable approaches, unsupervised and domain independent solutions further increases the complexity of this task. Currently, existing techniques only partially solve the problem and have several limitations. In this paper, we propose a novel methodology of descriptive text mining, capable of offering accurate explanations in unsupervised settings and of quantifying the results based on their statistical significance. Considering the strong growth of patient communities on social platforms such as Facebook, we demonstrate the effectiveness of the contribution by taking the short social posts related to Esophageal Achalasia as a typical case study. Specifically, the methodology produces useful explanations about the experiences of patients and caregivers. Starting directly from the unlabeled patients posts, we derive correct scientific correlations among symptoms, drugs, treatments, foods and so on. Copyright © 2020 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved.

关键词： Semantics

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Accuracy of synchrophasor measurements provided by the sine-fit algorithms

Accuracy of synchrophasor measurements provided by the sine-...

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2012 IEEE International Energy Conference and Exhibition, ENERGYCON 2012

作者： Belega, Daniel Petri, Dario Faculty of Electronics and Telecommunications Politehnica University of Timisoara Romania DISI Department of Information Engineering and Computer Science University of Trento Italy

ISBN: (纸本)9781467314541

The paper analyzes the accuracies of both the half-cycle and one-cycle synchrophasor estimators provided by the threeand four-parameter sine-fit algorithms when off-nominal frequency offset, amplitude modulation, and phase modulation occur. The test conditions comply with the IEEE Standard C37.118.1-2011 for synchrophasor measurements for power systems. The algorithm accuracy is evaluated in terms of the Total Vector Errors (TVEs) expressed as a function of the relative error in the a-priori available sine-wave frequency estimate used as input to the algorithms. The achieved TVEs are compared with the related accuracy threshold specified in the Standard. From this comparison some interesting conclusions concerning advantages achieved by applying the sine-fit algorithms to synchrophasor measurements are drawn. © 2012 IEEE.

关键词： IEEE Standards

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Blending BDI Agents with Object-Oriented and Functional Programming with JaKtA

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SN computer science 2024年第8期5卷 1-24页

作者： Baiardi, Martina Burattini, Samuele Ciatto, Giovanni Pianini, Danilo Department of Computer Science and Engineering (DISI) Alma Mater Studiorum Universitá di Bologna Via dell’Universitá 50 FC Cesena 47522 Italy

The popularity of multi-paradigm languages is on the rise, enabling developers to select the most appropriate paradigm for each task. While object-oriented and functional programming are commonly combined, other paradigms can also be hybridized. This paper introduces JaKtA, an internal Domain-Specific Language designed to support the definition of Belief-Desire-Intention agents in Kotlin. Our work represents an initial exploration into blending Agent-Oriented Programming with other prevalent paradigms, emphasizing the potential benefits of using internal Domain-Specific Languages. We demonstrate, through JaKtA, how this approach facilitates the creation of compact and expressive Belief-Desire-Intention agents that seamlessly integrate with the host language, its libraries, and tooling. © The Author(s) 2024.

关键词： AgentSpeak(L) BDI DSL JaKtA Kotlin

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Train in Austria, Race in Montecarlo: Generalized RL for Cross-Track F1tenthLIDAR-Based Races 19

Train in Austria, Race in Montecarlo: Generalized RL for Cro...

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19th IEEE Annual Consumer Communications and Networking Conference, CCNC 2022

作者： Bosello, Michael Tse, Rita Pau, Giovanni Università di Bologna DISI: Department of Computer Science and Engineering Cesena Italy School of Applied Sciences Macao Polytechnic Institute China Ucla Samueli Computer Science Department Los Angeles United States

ISBN: (纸本)9781665431620

Autonomous vehicles have received great attention in the last years, promising to impact a market worth billions. Nevertheless, the dream of fully autonomous cars has been delayed with current self-driving systems relying on complex processes coupled with supervised learning techniques. The deep reinforcement learning approach gives us newer possibilities to solve complex control tasks like the ones required by autonomous vehicles. It let the agent learn by interacting with the environment and from its mistakes. Unfortunately, RL is mainly applied in simulated environments, and transferring learning from simulations to the real world is a hard problem. In this paper, we use LIDAR data as input of a Deep Q-Network on a realistic 1/10 scale car prototype capable of performing training in real-time. The robot-driver learns how to run in race tracks by exploiting the experience gained through a mechanism of rewards that allow the agent to learn without human supervision. We provide a comparison of neural networks to find the best one for LIDAR data processing, two approaches to address the sim2real problem, and a detail of the performances of DQN in time-lap tasks for racing robots. © 2022 IEEE.

关键词： Real time systems

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Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition 33

Cluster-level pseudo-labelling for source-free cross-domain ...

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33rd British Machine Vision Conference Proceedings, BMVC 2022

作者： Conti, Alessandro Rota, Paolo Wang, Yiming Ricci, Elisa DISI Department of Information Engineering and Computer Science University of Trento Italy CIMeC - Center for Mind and Brain Sciences University of Trento Italy

Automatically understanding emotions from visual data is a fundamental task for human behaviour understanding. While models devised for Facial Expression Recognition (FER) have demonstrated excellent performances on many datasets, they often suffer from severe performance degradation when trained and tested on different datasets due to domain shift. In addition, as face images are considered highly sensitive data, the accessibility to large-scale datasets for model training is often denied. In this work, we tackle the above-mentioned problems by proposing the first Source-Free Unsupervised Domain Adaptation (SFUDA) method for FER. Our method exploits self-supervised pretraining to learn good feature representations from the target data and proposes a novel and robust cluster-level pseudo-labelling strategy that accounts for in-cluster statistics. We validate the effectiveness of our method in four adaptation setups, proving that it consistently outperforms existing SFUDA methods when applied to FER, and is on par with methods addressing FER in the UDA setting. Code is available at https://***/altndrr/clup. © 2022. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Face recognition

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Dynamical Criticality:Overview and Open Questions

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Journal of Systems science & Complexity 2018年第3期31卷 647-663页

作者： ROLI Andrea VILLANI Marco FILISETTI Alessandro SERRA Roberto Department of Computer Science and Engineering (DISI) Campus of Cesena University of Bologna Italy Department of Physics Informatics and Mathematics University of Modena and Reggio Emilia Italy European Centre for Living Technology Venezia Italy Explora s.r.l. Roma Italy & European Centre for Living Technology Venezia Italy

Systems that exhibit complex behaviours are often found in a particular dynamical con- dition, poised between order and disorder. This observation is at the core of the so-called criticality hypothesis, which states that systems in a dynamical regime between order and disorder attain the highest level of computational capabilities and achieve an optimal trade-off between robustness and flexibility. Recent results in cellular and evolutionary biology, ueuroscience and computer science have revitalised the interest in the criticality hypothesis, emphasising its role as a viable candidate general law in adaptive complex systems. This paper provides an overview of the works on dynamical criticality that are -- To the best of our knowledge -- Particularly relevant for the criticality hypothesis. The authors review the main contributions concerning dynamics and information processing at the edge of chaos, and illustrate the main achievements in the study of critical dynamics in biological systems. Finally, the authors discuss open questions and propose an agenda for future work.

关键词： Attractors criticality dynamical regimes edge of chaos phase transitions.

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A protocol performance comparison in modular WSNs for data center server monitoring

A protocol performance comparison in modular WSNs for data c...

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5th International Symposium on Industrial Embedded Systems, SIES 2010

作者： Sasidharan, Swaytha Pianegiani, Fernando MacIi, David DISI -University of Trento Via Sommarive 14 38100 Trento Italy Italy Department of Information Engineering and Computer Science University of Trento Italy

Industrial applications based on Wireless Sensor Networks (WSNs) have three main desirable requirements, i.e. low end-to-end latency, low packet loss and low power consumption. Such parameters depend on the network topology as well as on the protocol used to collect data. In the case of WSNs for server monitoring in large data centers, a modular clustertree topology is the preferable solution due to the intrinsically clustered nature of this application. However, choosing the most efficient and reliable data collection protocol is not an easy task. In this paper, three protocols for WSNs (i.e. CTP, MultiHopLQI and BLIP 6LowPAN) are experimentally compared with the purpose to assess the performances in terms of latency and packet loss. The obtained results, although preliminary, represent a good starting point to determine the best protocol for WSNs with a modular cluster-tree topology. © 2010 IEEE.

关键词： Wireless sensor networks

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