The Harmonic Tunneling Tag: a Dual-Band Approach to Backscattering Communications

International audienceAs an answer to the self-interference problem inherent to RFID systems, this work proposes a dual-band backscat-tering architecture. A dual-band RFID system architecture can bring several advantages to the RFID technology. In fact, a dual-band reader could operate without any self-interference cancellation circuit that currently limits its sensitivity; moreover, its dual-band architecture would be compatible with software defined radio-based cellphones. Dual-band readers will need to talk with low-powered dual-band tags that up-convert, modulate, and backscatter the impinging signal from the fundamental frequency to the 2 nd harmonic without weakening the communication link. This article reports on the UHF dual-band Harmonic Tun-neling Tag capable of backscattering and amplifying a 900 MHz signal when receiving an input carrier at 450 MHz. The Harmonic Tunneling Tag provides positive conversion gains (+7 dB) that improve the communication link by a factor of 2 and operates under a very low bias voltage of 0.16 V

SAI, a Sensible Artificial Intelligence that plays Go

We propose a multiple-komi modification of the AlphaGo Zero/Leela Zero paradigm. The winrate as a function of the komi is modeled with a two-parameters sigmoid function, so that the neural network must predict just one more variable to assess the winrate for all komi values. A second novel feature is that training is based on self-play games that occasionally branch -- with changed komi -- when the position is uneven. With this setting, reinforcement learning is showed to work on 7x7 Go, obtaining very strong playing agents. As a useful byproduct, the sigmoid parameters given by the network allow to estimate the score difference on the board, and to evaluate how much the game is decided.Comment: Updated for IJCNN 2019 conferenc

Enabling IoT stream management in multi-cloud environment by orchestration

(c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Every-Day lives are becoming increasingly instrumented by electronic devices and any kind of computer-based (distributed) service. As a result, organizations need to analyse an enormous amounts of data in order to increase their incomings or to improve their services. Anyway, setting-up a private infrastructure to execute analytics over Big Data is still expensive. The exploitation of Cloud infrastructure in IoT Stream management is appealing because of costs reductions and potentiality of storage, network and computing resources. The Cloud can consistently reduce the cost of analysis of data from different sources, opening analytics to big storages in a multi-cloud environment. Anyway, creating and executing this kind of service is very complex since different resources have to be provisioned and coordinated depending on users' needs. Orchestration is a solution to this problem, but it requires proper languages and methodologies for automatic composition and execution. In this work we propose a methodology for composition of services used for analyses of different IoT Stream and, in general, Big Data sources: in particular an Orchestration language is reported able to describe composite services and resources in a multi-cloud environment.Peer ReviewedPostprint (author's final draft

Generation of game contents by social media analysis and MAS planning

In the age of pervasive computing and social networks, it has become commonplace to retrieve opinions about digital contents in games. In the case of multi-player, open world gaming, in fact even in “old-school” single players games, it is evident the need for adding new features in a game depending on users comments and needs. However this is a challenging task that usually requires considerable design and programming efforts, and more and more patches to games, with the inevitable consequence of loosing interest in the game by players over years. This is particularly a hard problem for all games that do not intend to be designed as interactive novels. Process Content Generation (PCG) of new contents could be a solution to this problem, but usually such techniques are used to design new maps or graphical contents. Here we propose a novel PCG technique able to introduce new contents in games by means of new story-lines and quests. We introduce new intelligent agents and events in the world: their attitudes and behaviors will promote new actions in the game, leading to the involvement of players in new gaming content. The whole methodology is driven by Social Media Analysis contents about the game, and by the use of formal planning techniques based on Multi-Agents modelsPeer ReviewedPostprint (author's final draft

Multiparametric Investigation of Dynamics in Fetal Heart Rate Signals

In the field of electronic fetal health monitoring, computerized analysis of fetal heart rate (FHR) signals has emerged as a valid decision-support tool in the assessment of fetal wellbeing. Despite the availability of several approaches to analyze the variability of FHR signals (namely the FHRV), there are still shadows hindering a comprehensive understanding of how linear and nonlinear dynamics are involved in the control of the fetal heart rhythm. In this study, we propose a straightforward processing and modeling route for a deeper understanding of the relationships between the characteristics of the FHR signal. A multiparametric modeling and investigation of the factors influencing the FHR accelerations, chosen as major indicator of fetal wellbeing, is carried out by means of linear and nonlinear techniques, blockwise dimension reduction, and artificial neural networks. The obtained results show that linear features are more influential compared to nonlinear ones in the modeling of HRV in healthy fetuses. In addition, the results suggest that the investigation of nonlinear dynamics and the use of predictive tools in the field of FHRV should be undertaken carefully and limited to defined pregnancy periods and FHR mean values to provide interpretable and reliable information to clinicians and researchers

Plantar pressure distribution analysis in normal weight young women and men with normal and claw feet: a cross-sectional study

We analyzed the plantar support in 72 normal-weight young voluntaries (46 women, 26 men), by a baropodometric platform. We considered subjects with claw foot (CFS) and subjects with normal foot (NFS). We found a significant reduction of total plantar support surface in the CFS (P < 0.0001 for women, P < 0.001 for men), due to the reduction of the forefoot and rear foot areas of both plantar imprints. Indeed, CFS of both sexes exhibited higher values of both plantar pressure and peak pressure, compared to the NFS. Moreover, the load per units of plantar surface increased in CFS compared to the NFS. In conclusion, the reduction of plantar support surfaces in CFS of both sexes was associated to a major load per units of plantar surface in the forefoot and rear foot areas, and this may be a risk factor to lower extremity overuse injuries

A Multistate Friction Model for the Compensation of the Asymmetric Hysteresis in the Mechanical Response of Pneumatic Artificial Muscles

These days, biomimetic and compliant actuators have been made available to the main applications of rehabilitation and assistive robotics. In this context, the interaction control of soft robots, mechatronic surgical instruments and robotic prostheses can be improved through the adoption of pneumatic artificial muscles (PAMs), a class of compliant actuators that exhibit some similarities with the structure and function of biological muscles. Together with the advantage of implementing adaptive compliance control laws, the nonlinear and hysteretic force/length characteristics of PAMs pose some challenges in the design and implementation of tracking control strategies. This paper presents a parsimonious and accurate model of the asymmetric hysteresis observed in the force response of PAMs. The model has been validated through the experimental identification of the mechanical response of a small-sized PAM where the asymmetric effects of hysteresis are more evident. Both the experimental results and a comparison with other dynamic friction models show that the proposed model could be useful to implement efficient compensation strategies for the tracking control of soft robots

Information in a network of neuronal cells: Effect of cell density and short-term depression

Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect