Search results for "LABOR"

Software Architectures for Human-Machine Interaction Using Natural Language

Il linguaggio naturale rappresenta un sistema di comunicazione a carattere inferenziale in opposizione ai sistemi di comunicazione a codice che non prevedono una forma di ragionamento intelligente da parte del ricevente, ma si basano sul riconoscimento di patterns dell'informazione. In un sistema di comunicazione di tipo inferenziale, infatti, si parte dal presupposto che il ricevente abbia una certa "intelligenza" e sia, quindi, capace di comprendere, elaborare ed inferire il contenuto informativo di una comunicazione attraverso ragionamenti su un background di conoscenze (come modelli di mondo e di linguaggio) condivisi sia dalla sorgente che dal destinatario. L'attività di ricerca, svolt…

Creation and cognition for humanoid live dancing

2016

Abstract Computational creativity in dancing is a recent and challenging research field in Artificial Intelligence and Robotics. We present a cognitive architecture embodied in a humanoid robot capable to create and perform dances driven by the perception of music. The humanoid robot is able to suitably move, to react to human mate dancers and to generate novel and appropriate sequences of movements. The approach is based on a cognitive architecture that integrates Hidden Markov Models and Genetic Algorithms. The system has been implemented on a NAO robot and tested in public setting-up live performances, obtaining positive feedbacks from the audience.

An automatic system for humanoid dance creation

2016

Abstract The paper describes a novel approach to allow a robot to dance following musical rhythm. The proposed system generates a dance for a humanoid robot through the combination of basic movements synchronized with the music. The system made up of three parts: the extraction of features from audio file, estimation of movements through the Hidden Markov Models and, finally, the generation of dance. Starting from a set of given movements, the robot choices sequence of movements a suitable Hidden Markov Model, and synchronize them processing musical input. The proposed approach has the advantage that movement execution probabilities could be changed according evaluation of the dance executi…

Too Much or Too Little Messaging? Situational Determinants of Guilt About Mobile Messaging

2021

Abstract Mobile messaging has been associated with guilt. Guilt about too much messaging may result from self-control failures during goal conflicts. Conversely, guilt about too little messaging may result from violating the salient norm to be available. This research considers both boundary conditions of guilt about mobile communication—goal conflicts and availability norm salience—simultaneously for the first time. We conducted two preregistered experiments to investigate their interplay. Results from a vignette experiment, but not from a laboratory experiment, support the hypotheses that goal conflicts trigger guilt about using messengers and that guilt about not using messengers arises …

A wiki task for first-year university students : the effect of scripting students' collaboration

2015

Abstract This study investigates the effect of a collaboration script - i.e. a set of instructions to improve collaboration between learning partners - for a wiki task. Participants were first-year university students in Educational Sciences ( N  = 186) collaborating in groups of five during a three-week period to create a wiki on peer assessment in education. Two conditions were contrasted: a scripted and a non-scripted condition. The effect of scripting was measured in four ways (questionnaires, log-file analyses, group product scores, and individual pre–post-test scores). Results show significant positive effects of scripting with respect to the collaborative group processes and students…

Learning to collaborate: Designing collaboration in a 3-D game environment

2006

To respond to learning needs, Computer-Supported Collaborative Learning (CSCL) must provide instructional support. The particular focus of this paper is on designing collaboration in a 3-D virtual game environment intended to make learning more effective by promoting student opportunities for interaction. The empirical experiment eScape, which encourages learners to solve problems collaboratively, is also presented. eScape is a design experiment, comprising both the process of designing a collaborative game environment and an empirical study where data is collected using a variety of methods and analysed, after which the findings and conclusions serve as a basis for further design work. By …

An efficient distributed algorithm for generating and updating multicast trees

2006

As group applications are becoming widespread, efficient network utilization becomes a growing concern. Multicast transmission represents a necessary lower network service for the wide diffusion of new multimedia network applications. Multicast transmission may use network resources more efficiently than multiple point-to-point messages; however, creating optimal multicast trees (Steiner Tree Problem in networks) is prohibitively expensive. This paper proposes a distributed algorithm for the heuristic solution of the Steiner Tree Problem, allowing the construction of effective distribution trees using a coordination protocol among the network nodes. Furthermore, we propose a novel distribut…

Energy Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds with Hybrid Receivers

2014

In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power transfer (SWIPT) receivers. The CMC, which consists of several collaborating MTs offers one potential solution for downlink content distribution and for the energy consumption reduction at the terminal side. Meanwhile, as RF signal can carry both information and energy simultaneously, the induced SWIPT has gained much attention for energy efficiency design of mobile nodes. Previous work on the design of CMC system mainly focused on the cloud formulation or en…

Information Assurance and Advanced Human-Computer Interfaces

2008

Fuzzy Clustering of Histopathological Images Using Deep Learning Embeddings

2021

Metric learning is a machine learning approach that aims to learn a new distance metric by increas- ing (reducing) the similarity of examples belonging to the same (different) classes. The output of these approaches are embeddings, where the input data are mapped to improve a crisp or fuzzy classifica- tion process. The deep metric learning approaches regard metric learning, implemented by using deep neural networks. Such models have the advantage to discover very representative nonlinear embed- dings. In this work, we propose a triplet network deep metric learning approach, based on ResNet50, to find a representative embedding for the unsupervised fuzzy classification of benign and maligna…