Auto-Associative Recurrent Neural Networks and Long Term Dependencies in Novelty Detection for Audio Surveillance Applications

Machine Learning applied to Automatic Audio Surveillance has been attracting increasing attention in recent years. In spite of several investigations based on a large number of different approaches, little attention had been paid to the environmental temporal evolution of the input signal. In this work, we propose an exploration in this direction comparing the temporal correlations extracted at the feature level with the one learned by a representational structure. To this aim we analysed the prediction performances of a Recurrent Neural Network architecture varying the length of the processed input sequence and the size of the time window used in the feature extraction. Results corroborated the hypothesis that sequential models work better when dealing with data characterized by temporal order. However, so far the optimization of the temporal dimension remains an open issu

The Design of UDOO Boards: Contributing to the Appropriation of Digital Technology

The domain of Human-Computer Interaction does not concern just the design of technology that is easy to use, useful, and fancy – it has to do with our role in shaping our environment, our ecological niche that today involves the whole earth. A key concept in the interaction between humans and computing resources is that of appropriation originally proposed by Aleksei Nikolaevich Leontiev. In the present paper we will first review the concept of appropriation and will present bricolage as a key activity for fostering appropriation. Then we will present the Makers Movement as a socio-cultural movement relevant for the process of appropriation of digital technology. Finally, we will describe our approach and vision in the design of the UDOO, a single board computer, and of a specific developing environment, UAPPI, for enabling the appropriation through meaningful activities of digital technologies

The AXIOM platform for next-generation cyber physical systems

Cyber-Physical Systems (CPSs) are widely used in many applications that require interactions between humans and their physical environment. These systems usually integrate a set of hardware-software components for optimal application execution in terms of performance and energy consumption. The AXIOM project (Agile, eXtensible, fast I/O Module), presented in this paper, proposes a hardware-software platform for CPS coupled with an easy parallel programming model and sufficient connectivity so that the performance can scale-up by adding multiple boards. AXIOM supports a task-based programming model based on OmpSs and leverages a high-speed, inexpensive communication interface called AXIOM-Link. The board also tightly couples the CPU with reconfigurable resources to accelerate portions of the applications. As case studies, AXIOM uses smart video surveillance, and smart home living applicationsThis work is partially supported by the European Union H2020 program through the AXIOM project (grant ICT-01-2014 GA 645496) and HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, and by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). We also thank the Xilinx University Program for its hardware and software donations.Peer ReviewedPostprint (author's final draft

UDOO App Inventor: Introducing Novices to the Internet of Things

This paper describes the opportunities provided by the new graphical tool UDOO App Inventor (UAPPI) for enhancing the programming learning experience. With this tool, coding and programming are no longer limited to screen pixels but will incorporate real objects in the physical world. The aim of the authors' research is to develop new tools for coding alphabetization, by focusing on live programming, event programming, physical computing and overcoming syntax obstacles by using blocks programming. They describe two simple Research through Design case studies carried out with different categories of attendees in order to illustrate the potential of the UAPPI platform. In the first case, the authors render a door interactive, while in the second, they build a simple rover

Some new details of the copper-hydrogen peroxide interaction

The addition of neocuproine (NC) or bathocuproine-disulphonate at the end of the autooxidation of Cu-I in phosphate buffer, pH 7.4, regenerates almost entirely the O-2 consumed. Other chelating agents assayed, including o-phenanthroline, cannot replace NC in promoting the O-2 formation. O-2 is also produced by adding NC to a mixture of Cu-II and H2O2 Concomitant with the O-2 evolution, the typical absorbance of the (NC)(2)Cu-I complex appears to account for the complete reduction of Cu-II to Cu-I. It is concluded that the addition of H2O2 with Cu-II produces the equilibrium Cu-II(O2H)(-) (CdO2H)-O-I.. Addition of NC shifts the equilibrium to the right side by binding CuI. The released O-2(.-) then reacts with the remaining Cu-II yielding, in the presence of NC, the net reaction of 4 NC + 2 Cu-II + H2O2 --> 2 (NC)(2)Cu-I + O-2 + 2 H+. O-2 is also released in the absence of added NC provided the H2O2 concentration is increased. In these conditions the Cu-II(O2H)(-) complex undergoes other reactions leading to the copper-catalysed decomposition of H2O2. (C) 1997 Academic Press

UAPPI: A platform for extending app inventor towards the worlds of loT and machine learning

This chapter describes the opportunities offered by an extension of MIT App Inventor 2 named UDOO App Inventor (UAPPI). UAPPI aims to facilitate learning in programming the behavior of objects in the physical world (e.g., internet of things). In addition, UAPPI offers the opportunity to experiment with the emerging field of interactive machine learning. Two case studies devoted to different user groups are described to illustrate these opportunities. In the first, dedicated to middle school students, a door is made interactive; in the second, aimed at interaction designers, a light source is controlled by the blink of the eyes and the smile intensity

Aminoethylcysteine ketimine decarboxylated dimer inhibits mitochondrial respiration by impairing electron transport at complex I level.

The product of the spontaneous dimerization and decarboxylation of aminoethylcysteine ketimine (simply named the dimer in this note) has been investigated for a possible biochemical activity. It has been found that the dimer inhibits the ADP-dependent oxidation of NAD+-linked substrates in rat liver mitochondria and electron transport from NADH to O2 in bovine heart submitochondrial particles (SMP). Oxidation of succinate by SMP is not impaired by concentrations of the dimer inhibiting almost totally NADH oxidation. Furthermore, the dimer did not affect the rotenone-insensitive electron transfer from NADH to menadione. These results give a preliminary indication suggesting that the dimer inhibits electron flow from NADH dehydrogenase to ubiquinone at or near the rotenone binding site(s). The dimer inhibition falls in the same range exibited by some neurotoxins which are known to interact with the rotenone binding site

Novel findings on the copper catalysed oxidation of cysteine

The oxidation of cysteine (RSH) has been studied by using O-2, ferricytochrome c (Cyt c) and nitro blue tetrazolium (NET) as electron accepters. The addition of 200 mu M Cu-II to a solution of 2 mM cysteine, pH 7.4, produces an absorbance with a peak at 260 nm and a shoulder at 300 nm. Generation of a cuprous bis-cysteine complex (RS-CuI-SR) is responsible for this absorbance. In the absence of O-2 the absorbance is stable for long time while in the presence of air it vanishes slowly only when the cysteine excess is consumed. The neocuproine assay and the EPR analysis show that the metal remains reduced in the course of the oxidation of cysteine returning to the oxidised form at the end of reaction when all RSH has been oxidised to RSSR. Addition of Cu-II enhances the reduction rate of Cyt c and of NET by cysteine also under anaerobiosis indicating the occurrence of a direct reduction of the acceptor by the complex. It is concluded that the cuprous bis-cysteine complex (RS-CuI-SR) is the catalytic species involved in the oxidation of cysteine. The novel finding of the stability of the complex together with the metal remaining in the reduced form during the oxidation suggest sulfur as the electron donor in the place of the metal ion

ATM Protection Using Embedded Deep Learning Solutions

Last decade advances in Deep Learning methods lead to sensible improvements in state of the art results in many real world applications, thanks to the exploitation of particular Artificial Neural Networks architectures. In this paper we present an investigation of the application of such kind of structures to a Video Surveillance case of study, in which the special nature and the small amount of available data increases the difficulties during the training phase. The analyzed scenario involves the protection of Automatic Teller Machines (ATM), representing a sensitive problem in the world of both banking and public security. Because of the critical issues related to this environment, even apparently small improvements in either accuracy or responsiveness of surveillance systems can produce a fundamental contribution. Even if the experimentation has been reproduced in an artificial scenario, the results show that the implemented architecture is able to classify depth data in real-time on an embedded system, detecting all the test attacks in a few seconds