Non-Volatile Memory Interface Protocols for Smart Sensor Networks and Mobile Devices

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Analog to Digital Conversion Methods for Smart Sensing Systems

The new capabilities of smart sensing systems namely, adaptability, reconfiguration, lowenergy consumption and cost, between others, require a wisely selection of the methods that are use to perform analog to digital conversion. It is very important to optimize the trade-offs between, resolution, accuracy, conversion rate, and energy consumption, between others, and above all to adapt dynamically the conversion parameters for different signals characteristics and applications\\u27 purposes. Establishing the best trade-offs are even more important when signals to be digitized have different signal-to-noise ratios (S/N) ratios, different requirements of measuring accuracy and acquisition rate, their characteristics are time-variant and above all if they are sharing the same digitalization device. Very low resolution or conversion rate of data acquisition (DAQs) systems are generally not compliant with measurement systems\\u27 requirements since signal information is lost without any possible recovery procedure. Otherwise, if resolution or data acquisition rate are excessively high that means the sampling rate is much higher than its minimum value (Nyquist rate), the excessive amplitude and time resolutions provided by A/D conversion or frequency-to-digital conversion (FDC) does not improve measurements system\\u27s performance. Moreover, the excessive resolution or data acquisition rate implies an increase of hardware and software complexity, data processing load and a higher implementation cost, without any benefits. So, for any A/D or FDC conversion method the best trade-off between different conversion characteristics must be established considering applications\\u27 purposes. For example, in wireless sensing and actuating networks (WSAN) energy wastes are particularly important because a wrong choice of conversion method can affect deeply measurement system autonomy. Whenever possible, classical A/D conversion methods are being replaced by discrete A/D conversion methods that are supported by low cost microcontroller (C) (Microchip, 2010) connected to a few external resistive or capacitive components. This solution takes full advantage of Cs benefits, namely specific hardware and software capabilities and it provides a conversion rate that can be higher that several hundreds of kHz that is sufficien

Inter-organizational information systems adoption for service innovation in building sector

The building sector has experienced a significant decline in recent years in Spain and Europe as a result of the financial crisis that began in 2007. This drop accompanies a low penetration of information and communication technologies in inter-organizational oriented business processes. The market decrease is causing a slowdown in the building sector, where only flexible small and medium enterprises (SMEs) survive thanks to specialization and innovation in services, which allow them to face new market demands. Inter-organizational information systems (IOISs) support innovation in services, and are thus a strategic tool for SMEs to obtain competitive advantage. Because of the inherent complexity of IOIS adoption, this research extends Kurnia and Johnston's (2000) theoretical model of IOIS adoption with an empirical model of IOIS characterization. The resultant model identifies the factors influencing IOIS adoption in SMEs in the building sector, to promote further service innovation for competitive and collaborative advantages. An empirical longitudinal study over six consecutive years using data from Spanish SMEs in the building sector validates the model, using the partial least squares technique and analyzing temporal stability. The main findings of this research are the four ways an IOIS might contribute to service innovation in the building sector. Namely: a) improving client interfaces and the link between service providers and end users; b) defining a specific market where SMEs can develop new service concepts; c) enhancing the service delivery system in traditional customer?supplier relationships; and d) introducing information and communication technologies and tools to improve information management

Male infertility in spinal cord trauma

Every year there are 10 thousand new cases of patients victimized by spinal cord trauma (SCT) in the United States and it is estimated that there are 7 thousand new cases in Brazil. Eighty percent of patients are fertile males. Infertility in this patient group is due to 3 main factors resulting from spinal cord lesions: erectile dysfunction, ejaculatory disorder and low sperm counts. Erectile dysfunction has been successfully treated with oral and injectable medications, use of vacuum devices and penile prosthesis implants. The technological improvement in penile vibratory stimulation devices (PVS) and rectal probe electro-ejaculation (RPE) has made such procedures safer and accessible to patients with ejaculatory dysfunction. Despite the normal number of spermatozoa found in semen of spinal cord-injured patients, their motility is abnormal. This change does not seem to be related to changes in scrotal thermal regulation, frequency of ejaculation or duration of spinal cord damage but to factors related to the seminal plasma. Despite the poor seminal quality, increasingly more men with SCT have become fathers through techniques ranging from simple homologous insemination to sophisticated assisted reproduction techniques such as intracytoplasmic sperm injection (ICSI).Universidade Federal de São Paulo (UNIFESP), Escola Paulista de Medicina (EPM) Department of UrologySan Francisco Home School Section of UrologyUNIFESP, EPM, Department of UrologySciEL

Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio

The growing usage of digital microphones has generated an increased interest in the topic of Acoustic Anomaly Detection (AAD). Indeed, there are several real-world AAD application domains, including working machines and in-vehicle intelligence (the main target of this research project). This paper introduces three deep AutoEncoders (AE) for unsupervised AAD tasks, namely a Dense AE, a Convolutional Neural Network (CNN) AE and Long Short-Term Memory Autoencoder (LSTM) AE. To tune the deep learning architectures, development data were adopted from public domain audio datasets related with working machines. A large set of computational experiments was held, showing that the three proposed deep autoencoders, when combined with a melspectrogram sound preprocessing, are quite competitive and outperform a recently proposed AE baseline. Next, on a second experimental stage, aiming to address the final in-vehicle passenger safety goal, the three AEs were adapted to learn from in-vehicle normal audio, assuming three realistic scenarios that were generated by a synthetic audio mixture tool. In general, a high quality AAD discrimination was obtained: working machine data - 72% to 91%; and in-vehicle audio - 78% to 81%. In conjunction with an automotive company, an in-vehicle AAD intelligent system prototype was further developed, aiming to test a selected model (LSTM AE) during a pilot demonstration event that targeted the cough anomaly. Interesting results were obtained, with the AAD system presenting a high cough classification accuracy (e.g., 100% for front seat locations).This work is supported by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) - Project no 039334; Funding Reference: POCI-01-0247-FEDER-039334

Evaluacion de la actividad antibacteriana y antifungica de cuatro especies de liquenes de la region del Maule, Chile

56 p.La zona central de Chile se ha declarado como uno de los “hotspots” mundiales de la biodiversidad. Dentro de esta área los bosques costeros y de la precordillera son hábitat para una variedad de flora de Líquenes. Estas especies sintetizan y acumulan metabolitos secundarios, que no han sido estudiados en el área de la salud médica. Además, en esta región como en el resto del país, se observa un aumento en la resistencia a drogas rutinarias por parte de patógenos intrahospitalarios, generando en los pacientes una recuperación difícil y lenta. Esta evidencia dio origen al estudio para evaluar la actividad antibacteriana y antifúngica de extractos acuosos y alcohólicos de cuatro especies de líquenes nativos chilenos: Ramalina chilensis, Parmotrema chínense, Ramalina farinácea y Usnea sp.. En pruebas de ensayos los extractos (acuosos y alcohólicos) demostraron una variable gama de actividad antibacteriana a cuatro cepas de dos bacterias Gram positivas (Staphylococcus aureus, Enterococcus faecalis) y ninguna acción a cuatro cepas de dos bacterias Gram negativas (Pseudomonas aeruginosa y Escherichia coli ) y levaduras (Candida albicans y Saccharomyces cerevisiae). Los extractos alcohólicos, resuspendidos en agua, demostraron una mejor actividad antibacteriana que los extractos acuosos probados directamente con los patógenos (30% más alto). La identificación de los compuestos del extracto se utilizó ESI-MS (Electrospray Ionization Mass Spectrometry) y TLC-MALDI (Matriz assisted laser desorption/ionization) que para P. chínense fueron: ácido úsnico, ácido ramalinólico y atranol; En R. chilensis se encontró: ácido lecanórico, ácido divaricático y usnetol; y en Usnea sp.: parietina; y para R. farinácea: no se llego a una identificación. Para la mayoría de estos compuestos se ha descrito una actividad antibiótica contra agentes patógenos agresivos. En conclusión, los resultados indican que los compuestos en tres especies de líquenes representan una potencial fuente de antibióticos natural que podría contribuir a la solución de problemas en el área farmacológica. Además, la actividad antibacteriana demuestra un mérito razonable para continuar una investigación adicional dirigida a otras especies liquénicas, como también en otras especies nativas de la zona central

Educational data mining for tutoring support in Higher Education: a web-based tool case study in engineering degrees

This paper presents a web-based software tool for tutoring support of engineering students without any need of data scientist background for usage. This tool is focused on the analysis of students' performance, in terms of the observable scores and of the completion of their studies. For that purpose, it uses a data set that only contains features typically gathered by university administrations about the students, degrees and subjects. The web-based tool provides access to results from different analyses. Clustering and visualization in a low-dimensional representation of students' data help an analyst to discover patterns. The coordinated visualization of aggregated students' performance into histograms, which are automatically updated subject to custom filters set interactively by an analyst, can be used to facilitate the validation of hypotheses about a set of students. Classification of students already graduated over three performance levels using exploratory variables and early performance information is used to understand the degree of course-dependency of students' behavior at different degrees. The analysis of the impact of the student's explanatory variables and early performance in the graduation probability can lead to a better understanding of the causes of dropout. Preliminary experiments on data of the engineering students from the 6 institutions associated to this project were used to define the final implementation of the web-based tool. Preliminary results for classification and drop-out were acceptable since accuracies were higher than 90% in some cases. The usefulness of the tool is discussed with respect to the stated goals, showing its potential for the support of early profiling of students. Real data from engineering degrees of EU Higher Education institutions show the potential of the tool for managing high education and validate its applicability on real scenarios.This work was supported by the Erasmus+ Key Action 2 Strategic Partnerships KA203, funded by the European Commission, under Grant 2016-1-ES01-KA203-025452.info:eu-repo/semantics/publishedVersio

Software product line engineering: a practical experience

The lack of mature tool support is one of the main reasons that make the industry to be reluctant to adopt Software Product Line (SPL) approaches. A number of systematic literature reviews exist that identify the main characteristics offered by existing tools and the SPL phases in which they can be applied. However, these reviews do not really help to understand if those tools are offering what is really needed to apply SPLs to complex projects. These studies are mainly based on information extracted from the tool documentation or published papers. In this paper, we follow a different approach, in which we firstly identify those characteristics that are currently essential for the development of an SPL, and secondly analyze whether the tools provide or not support for those characteristics. We focus on those tools that satisfy certain selection criteria (e.g., they can be downloaded and are ready to be used). The paper presents a state of practice with the availability and usability of the existing tools for SPL, and defines different roadmaps that allow carrying out a complete SPL process with the existing tool support.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Magic P12-TIC1814, HADAS TIN2015-64841-R (cofinanciado con fondos FEDER), MEDEA RTI2018-099213-B-I00 (cofinanciado con fondos FEDER), TASOVA MCIU-AEI TIN2017-90644-RED