Spiking neural networks trained with backpropagation for low power neuromorphic implementation of voice activity detection

Recent advances in Voice Activity Detection (VAD) are driven by artificial and Recurrent Neural Networks (RNNs), however, using a VAD system in battery-operated devices requires further power efficiency. This can be achieved by neuromorphic hardware, which enables Spiking Neural Networks (SNNs) to perform inference at very low energy consumption. Spiking networks are characterized by their ability to process information efficiently, in a sparse cascade of binary events in time called spikes. However, a big performance gap separates artificial from spiking networks, mostly due to a lack of powerful SNN training algorithms. To overcome this problem we exploit an SNN model that can be recast into an RNN-like model and trained with known deep learning techniques. We describe an SNN training procedure that achieves low spiking activity and pruning algorithms to remove 85% of the network connections with no performance loss. The model achieves state-of-the-art performance with a fraction of power consumption comparing to other methods.Comment: 5 pages, 2 figures, 2 table

Simultaneous state initialization and gyroscope bias calibration in visual inertial aided navigation

State of the art approaches for visual-inertial sensor fusion use filter-based or optimization-based algorithms. Due to the nonlinearity of the system, a poor initialization can have a dramatic impact on the performance of these estimation methods. Recently, a closed-form solution providing such an initialization was derived in [1]. That solution determines the velocity (angular and linear) of a monocular camera in metric units by only using inertial measurements and image features acquired in a short time interval. In this letter, we study the impact of noisy sensors on the performance of this closed-form solution. We show that the gyroscope bias, not accounted for in [1], significantly affects the performance of the method. Therefore, we introduce a new method to automatically estimate this bias. Compared to the original method, the new approach now models the gyroscope bias and is robust to it. The performance of the proposed approach is successfully demonstrated on real data from a quadrotor MAV

Seismic and Thermal Retrofitting of Masonry Buildings with Fiber Reinforced Composite Systems: A State of the Art Review

Old masonry buildings represent the largest part of traditional constructions. Generally, they are both seismically vulnerable and thermally dispersive. Therefore, the need for seismic and thermal retrofitting aimed at reducing their vulnerability and environmental impact has motivated research efforts towards sustainable retrofitting solutions. This study presents a literature review of the approaches currently available for masonry retrofitting. Specifically, it highlights the use of fiber in textile form i.e., Textile Reinforcement Mortar (TRM), as Fiber Reinforced Polymer (FRP) and natural fibers (animal and plant sources) to masonry retrofitting. In addition, specific attention is devoted to the integrated (structural and thermal) fiber-based integrated retrofitting techniques that are becoming very important in the last years

Expand-and-Cluster: Exact Parameter Recovery of Neural Networks

Can we recover the hidden parameters of an Artificial Neural Network (ANN) by probing its input-output mapping? We propose a systematic method, called `Expand-and-Cluster' that needs only the number of hidden layers and the activation function of the probed ANN to identify all network parameters. In the expansion phase, we train a series of networks of increasing size using the probed data of the ANN as a teacher. Expansion stops when a minimal loss is consistently reached in networks of a given size. In the clustering phase, weight vectors of the expanded students are clustered, which allows structured pruning of superfluous neurons in a principled way. We find that an overparameterization of a factor four is sufficient to reliably identify the minimal number of neurons and to retrieve the original network parameters in $80\%$ of tasks across a family of 150 toy problems of variable difficulty. Furthermore, shallow and deep teacher networks trained on MNIST data can be identified with less than $5\%$ overhead in the neuron number. Thus, while direct training of a student network with a size identical to that of the teacher is practically impossible because of the highly non-convex loss function, training with mild overparameterization followed by clustering and structured pruning correctly identifies the target network.Comment: Preprint: 14 pages, 6 figures. Appendix: 8 pages, 7 figure

Autonomic Management of Networked Small-Medium Factories

The Chapter reports the achievements of a research project that is developing a software platform with a suite of autonomic services enabling every company in the network to move from a situation where it wastes valuable resources in struggling with its customers and suppliers, towards a rational business environment where communication becomes faster, and operation and collaboration more efficient. The ultimate objective of the project is to set-up, develop, experiment and promote the adoption of a new collaboration practice within networked factories taking advantage of the autonomic model applied to a suite of support software services

Sustainable Retrofitting Solutions: Evaluating the Performance of Jute Fiber Nets and Composite Mortar in Natural Fiber Textile Reinforced Mortars

Sustainable building materials for integrated (structural and thermal) retrofitting are the need of the hour to retrofit/upgrade the seismic vulnerable and ill-insulated existing building stocks. At the same time, the use of natural fibers and their recyclability could help construct safer and more sustainable buildings. This paper presents three aspects of jute fiber products: (1) the evaluation of the mechanical performance of the jute nets (2.5 cm × 2.5 cm and 2.5 cm and 1.25 cm mesh configurations) through tensile strength tests (with the aim for these to be used in upgrading masonry wall with natural fiber textile reinforced mortars (NFTRM) systems); (2) the hundred percentage recyclability of left-over jute fibers (collected during the net fabrication and failed nets post-tensile strength tests) for the composite mortar preparation; (3) and the evaluation of insulation capacity of the recycled jute net fiber composite mortar (RJNFCM) through thermal conductivity (TC) measurements, when a maximum amount of 12.5% of recycled jute fiber could be added in the mortar mixture at laboratory conditions and with available instruments Notably, when more than the said amount was used, the fiber–mortar bonding was found to be not optimal for the composite mortar preparation. These studies have been carried out considering these products’ applicability for integrated retrofitting purposes. It has been found that the denser mesh configuration (2.5 cm × 1.25 cm) is 35.80% stiffer than the other net configurations (2.5 cm × 2.5 cm). Also, the mesh configuration (2.5 cm × 1.25 cm) shows about 60% more capability to absorb strain energy. TC tests have demonstrated the moderate insulation capacity of these composite mortar samples, and the TC values obtained from the tests range from 0.110 (W/mK) to 0.121 (W/mK)

Osteology and phylogenetic relationships of Ligabuesaurus leanzai (Dinosauria: Sauropoda) from the Early Cretaceous of the Neuquén Basin, Patagonia, Argentina

Osteological knowledge of the sauropod dinosaur Ligabuesaurus leanzai is increased by the description of new postcranial elements assigned to the holotype MCF-PVPH-233. Furthermore, a newly referred specimen, MCF-PVPH-228, is recognized after a detailed revision of the abundant sauropod material collected from the Lohan Cura Formation outcrops in the Cerro de los Leones locality (southern Neuquén Basin, Patagonia, Argentina). Recent laboratory preparation and fieldwork allowed us to recognize several new morphological features of the pectoral and pelvic girdles and the cervical and caudal anatomy. Thus, a new diagnosis of Ligabuesaurus is proposed that includes new autapomorphies and a unique combination of features. A phylogenetic analysis based on this new material recovers Ligabuesaurus as a non-titanosaurian somphospondylan, more derived than Sauroposeidon. Therefore, we discuss the palaeobiogeographical implications for the diversification and distribution of South American somphospondylans, especially in the Neuquén Basin, which are closely related to the early stages of evolution of Titanosauria. In this context, Ligabuesaurus represents one of the more complete Early Cretaceous Titanosauriformes and the earliest non-titanosaurian somphospondylan of South America. Finally, the new information on Ligabuesaurus contributes not only to reconstruction of the sauropod faunal composition of south-western Gondwana, but also sheds light on the early stages and emergence of titanosaurians.Fil: Bellardini, Flavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigación en Paleobiología y Geología; ArgentinaFil: Coria, Rodolfo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigación en Paleobiología y Geología; Argentina. Provincia del Neuquén. Municipalidad de Plaza Huincul. Museo "Carmen Funes"; ArgentinaFil: Pino, Diego Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigación en Paleobiología y Geología; ArgentinaFil: Windholz, Guillermo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigación en Paleobiología y Geología; ArgentinaFil: Baiano, Mattia Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Provincia del Neuquén. Municipalidad de Villa El Chocón. Museo Paleontológico "Ernesto Bachmann"; Argentina. Universidad Nacional de Río Negro; ArgentinaFil: Martinelli, Agustín Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; Argentin

Development of terphenyl-2-methyloxazol-5(4H)-one derivatives as selective reversible MAGL inhibitors

Monoacylglycerol lipase is a serine hydrolase that plays a major role in the degradation of the endocannabinoid neurotransmitter 2-arachidonoylglycerol. A wide number of MAGL inhibitors are reported in literature; however, many of them are characterised by an irreversible mechanism of action and this behavior determines an unwanted chronic MAGL inactivation, which acquires a functional antagonism of the endocannabinoid system. The possible use of reversible MAGL inhibitors has only recently been explored, due to the lack of known compounds possessing efficient reversible inhibitory activities. In this work, we report a new series of terphenyl-2-methyloxazol-5(4H)-one derivatives characterised by a reversible MAGL-inhibition mechanism. Among them, compound 20b showed to be a potent MAGL reversible inhibitor (IC50= 348 nM) with a good MAGL/FAAH selectivity. Furthermore, this compound showed antiproliferative activities against two different cancer cell lines that overexpress MAGL

Observation of J/ψpJ/\psi p resonances consistent with pentaquark states in Λb0→J/ψK−p{\Lambda_b^0\to J/\psi K^-p} decays

Observations of exotic structures in the $J/\psi p$ channel, that we refer to as pentaquark-charmonium states, in $\Lambda_b^0\to J/\psi K^- p$ decays are presented. The data sample corresponds to an integrated luminosity of 3/fb acquired with the LHCb detector from 7 and 8 TeV pp collisions. An amplitude analysis is performed on the three-body final-state that reproduces the two-body mass and angular distributions. To obtain a satisfactory fit of the structures seen in the $J/\psi p$ mass spectrum, it is necessary to include two Breit-Wigner amplitudes that each describe a resonant state. The significance of each of these resonances is more than 9 standard deviations. One has a mass of $4380\pm 8\pm 29$ MeV and a width of $205\pm 18\pm 86$ MeV, while the second is narrower, with a mass of $4449.8\pm 1.7\pm 2.5$ MeV and a width of $39\pm 5\pm 19$ MeV. The preferred $J^P$ assignments are of opposite parity, with one state having spin 3/2 and the other 5/2.Comment: 48 pages, 18 figures including the supplementary material, v2 after referee's comments, now 19 figure