Dynamic Resource Reservation and Connectivity Tracking to Support Real-Time Communication among Mobile Units

Wireless communication technology is spreading quickly in almost all the information technology areas as a consequence of a gradual enhancement in quality and security of the communication, together with a decrease in the related costs. This facilitates the development of relatively low-cost teams of autonomous (robotic) mobile units that cooperate to achieve a common goal. Providing real-time communication among the team units is highly desirable for guaranteeing a predictable behavior in those applications in which the robots have to operate autonomously in unstructured environments. This paper proposes a MAC protocol for wireless communication that supports dynamic resource reservation and topology management for relatively small networks of cooperative units (10–20 units). The protocol uses a slotted time-triggered medium access transmission control that is collision-free, even in the presence of hidden nodes. The transmissions are scheduled according to the earliest deadline first scheduling policy. An adequate admission control guarantees the timing constraints of the team communication requirements, including when new nodes dynamically join or leave the team. The paper describes the protocol focusing on the consensus procedure that supports coherent changes in the global system. We also introduce a distributed connectivity tracking mechanism that is used to detect network partition and absent or crashed nodes. Finally, a set of simulation results are shown that illustrate the effectiveness of the proposed approaches

Role revolution: towards a new meaning of positions in basketball

Most team sports are characterized by positions to which the players in a team are assigned. The goal of this classification is to attribute specific responsibilities during a game. Moreover, the same classification drives the buying and selling of players according to team managers and coaches strategies. The existing positions - often defined a long time ago - tend to reflect traditional points of view about the game and sometimes they are no longer well-suited to the new concepts arisen with the evolution of the way of playing.   This paper focuses on basketball and aims at describing new roles of players during the game, by means of the analysis of players' performance statistics with data mining and machine learning tools. In detail, self-organizing maps and fuzzy clustering procedures are adopted in tandem to define groups of players with similar way of playing. The results show that, when considering the modern basketball players' statistics, classical positions are not able to fully represent their way of playing, and a new set of 5 roles emerges as a meaningful classification of players' characteristics

Opportunities for Web-Based Indicators in Environmental Sciences

This paper proposes a set of web-based indicators for quantifying and ranking the relevance of terms related to key-issues in Ecology and Sustainability Science. Search engines that operate in different contexts (e.g. global, social, scientific) are considered as web information carriers (WICs) and are able to analyse; (i) relevance on different levels: global web, individual/personal sphere, on-line news, and culture/science; (ii) time trends of relevance; (iii) relevance of keywords for environmental governance. For the purposes of this study, several indicators and specific indices (relational indices and dynamic indices) were applied to a test-set of 24 keywords. Outputs consistently show that traditional study topics in environmental sciences such as water and air have remained the most quantitatively relevant keywords, while interest in systemic issues (i.e. ecosystem and landscape) has grown over the last 20 years. Nowadays, the relevance of new concepts such as resilience and ecosystem services is increasing, but the actual ability of these concepts to influence environmental governance needs to be further studied and understood. The proposed approach, which is based on intuitive and easily replicable procedures, can support the decision-making processes related to environmental governance

Role revolution: towards a new meaning of positions in basketball

Most team sports are characterized by positions to which the players in a team are assigned. The goal of this classification is to attribute specific responsibilities during a game. Moreover, the same classification drives the buying and selling of players according to team managers and coaches strategies. The existing positions - often defined a long time ago - tend to reflect traditional points of view about the game and sometimes they are no longer well-suited to the new concepts arisen with the evolution of the way of playing.   This paper focuses on basketball and aims at describing new roles of players during the game, by means of the analysis of players' performance statistics with data mining and machine learning tools. In detail, self-organizing maps and fuzzy clustering procedures are adopted in tandem to define groups of players with similar way of playing. The results show that, when considering the modern basketball players' statistics, classical positions are not able to fully represent their way of playing, and a new set of 5 roles emerges as a meaningful classification of players' characteristics

Online Fall Detection using Recurrent Neural Networks

Unintentional falls can cause severe injuries and even death, especially if no immediate assistance is given. The aim of Fall Detection Systems (FDSs) is to detect an occurring fall. This information can be used to trigger the necessary assistance in case of injury. This can be done by using either ambient-based sensors, e.g. cameras, or wearable devices. The aim of this work is to study the technical aspects of FDSs based on wearable devices and artificial intelligence techniques, in particular Deep Learning (DL), to implement an effective algorithm for on-line fall detection. The proposed classifier is based on a Recurrent Neural Network (RNN) model with underlying Long Short-Term Memory (LSTM) blocks. The method is tested on the publicly available SisFall dataset, with extended annotation, and compared with the results obtained by the SisFall authors.Comment: 6 pages, ICRA 201

Coordinating distributed autonomous agents with a real-time database: the CAMBADA project

DETIInterest on using mobile autonomous agents has been growing, recently, due to their capacity to cooperate for diverse purposes, from rescue to demining and security. However, such cooperation requires the exchange of state data that is time sensitive and thus, applications should be aware of data temporal coherency. In this paper we describe the architecture of the agents that constitute the CAMBADA robotic soccer team developed at the University of Aveiro, Portugal. This architecture is built around a real-time database that is partially replicated in all team members and contains both local and remote state variables. The temporal coherency of the data is enforced by an adequate management system that refreshes each database item transparently at a rate specified by the application. The application software accesses the state variables of all agents with local operations, only, delivering both value and temporal coherency

Fifty Hertz electromagnetic field exposure stimulates secretion of β-amyloid peptide in cultured human neuroglioma

Recent epidemiological studies raise the possibility that individuals with occupational exposure to low frequency (50-60 Hz) electromagnetic fields (LF-EMF), are at increased risk of Alzheimer's disease (AD). However, the mechanisms through which LF-EMF may affect AD pathology are unknown. We here tested the hypothesis that the exposure to LF-EMF may affect amyloidogenic processes. We examined the effect of exposure to 3.1 mT 50 Hz LF-EMF on Abeta secretion in H4 neuroglioma cells stably overexpressing human mutant amyloid precursor protein. We found that overnight exposure to LF-EMF induces a significant increase of amyloid-beta peptide (Abeta) secretion, including the isoform Abeta 1-42, without affecting cell survival. These findings show for the first time that exposure to LF-EMF stimulates Abeta secretion in vitro, thus alluding to a potential link between LF-EMF exposure and APP processing in the brain