Thermoacoustic Emission from Carbon Nanotubes Imaged by Atomic Force Microscopy

The thermoacoustic effect of isolated single‐wall carbon nanotubes aligned between electrodes is experimentally observed for the first time by imaging the emitted acoustic wave using an atomic force microscopy‐based technique specifically developed for the task. The capability of such a technique for single‐point thermoacoustic measurements is first verified on carbon nanotubes layers with two electrodes for injecting alternate electric current. The technique is then demonstrated to allow the acquisition, simultaneously with the topography, of images reflecting the pressure of the acoustic wave at fixed distance from the sample. Such a capability is used to collect images reflecting the amplitude of acoustic waves generated by isolated nanotubes and nanotube bundles by the thermoacoustic effect.     

A Low-Cost and Low-Power Messaging System Based on the LoRa Wireless Technology

Mobile Networks and Applications - In this paper we describe a low-cost and low-power consumption messaging system based on LoRa technology. More that one billion people worldwide cannot access...     

Performance evaluation of an adaptive GSM receiver with frequency-selective fading and adjacent- and co-channel interference

This study represents the sequel and conclusion of a previous one already published in this Journal a few issues ago.¹ In that article, we tackled the problem of evaluating theoretically the performance of an adaptive MLSE receiver for MSK signals on a frequency-selective stationary radio propagation channel, and we validated the theoretical findings (in the form of upper and lower bounds to the BER of the receiver) by means of computer simulations. In the present paper, we report on the performance of the very same scheme of channel-estimator-plus-Viterbi-equalizer receiver for mobile communications in a more realistic operating environment. In particular, we completely encompass here the groupe spécial mobile (GSM) transmission format, based on the Gaussian minimum shift keying (GMSK) modulation scheme and on narrowband time-division multiple access (TDMA) transmission. Also, we remove the assumption of a time-invariant propagation channel, assuming the recommended standard GSM channels as benchmark transmission conditions. Finally, with the aid of extensive computer simulations, we analyse the sensitivity of the MLSE receiver to unwanted co-channel and adjacent-channel interference coming from other users of the mobile cellular GSM system.     

A new method for the analysis of integrated transmission lines

A flexible and efficient technique for the analysis of transmission lines is described. The transmission line is considered as the union of « elementary waveguides », where the medium is uniformly stratified. The modes are determined by matching the field at the interfaces using a procedure that leads to a linear eigenvalue problem involving a limited number of variables.     

Applied data science in patient-centric healthcare: Adaptive analytic systems for empowering physicians and patients

We define the emerging research field of applied data science as the knowledge discovery process in which analytic systems are designed and evaluated to improve the daily practices of domain experts. We investigate adaptive analytic systems as a novel research perspective of the three intertwining aspects within the knowledge discovery process in healthcare: domain and data understanding for physician- and patient-centric healthcare, data preprocessing and modelling using natural language processing and (big) data analytic techniques, and model evaluation and knowledge deployment through information infrastructures. We align these knowledge discovery aspects with the design science research steps of problem investigation, treatment design, and treatment validation, respectively. We note that the adaptive component in healthcare system prototypes may translate to data-driven personalisation aspects including personalised medicine. We explore how applied data science for patient-centric healthcare can thus empower physicians and patients to more effectively and efficiently improve healthcare. We propose meta-algorithmic modelling as a solution-oriented design science research framework in alignment with the knowledge discovery process to address the three key dilemmas in the emerging “post-algorithmic era” of data science: depth versus breadth, selection versus configuration, and accuracy versus transparency.     

Evidence of Oxygen Ferromagnetism in ZnO Based Materials

Discoveries of room‐temperature ferromagnetism (RTFM) in semiconductors hold great promise in future spintronics technologies. Unfortunately, this ferromagnetism remains poorly understood and the debate concerning the nature, carrier‐mediated versus defect‐mediated, of this ferromagnetism in semiconducting oxides is still open. Here, by using X‐ray absorption (XAS) and X‐ray magnetic circular dichroism (XMCD), it is demonstrated that the oxygen ions have a ferromagnetic response in different ZnO‐based compounds showing RTFM behavior: ZnO nanoparticles capped with organic molecules and ZnO/ZnS heterostructures. These results demonstrate the intrinsic occurrence of RTFM in these systems, and point out that it is not related to the metallic cation but it relays on the conduction band of the semiconductor.     

Reliable M2M/IoT data delivery from FANETs via satellite

The use of unmanned aerial vehicles (UAVs) is rising in several application fields. This work deals with the communication challenges in UAV swarms, or flying ad hoc network (FANET), when taking into account non–line‐of‐sight scenarios. The use of satellites is a necessity in such operating conditions; thus, this work provides architectural considerations and performance assessments when several (FANETs) share an uplink random access satellite channel, fed with M2M/IoT traffic generated from on‐board sensors, to be reliably delivered to a remote ground destination.     

Effect of thermal aging on the interfacial structure of SnAgCu solder joints on Cu

Interfacial structure plays a great role in solder joint reliability. In solder joints on Cu, not only is Kirkendall voiding at the solder/Cu interface a concern, but also the growth of interfacial Cu–Sn intermetallic compounds (IMCs). In this work, evolution of microstructure in the interfacial region was studied after thermal aging at 100–150 °C for up to 1000 h. Special effort was made during sample preparation to reveal details of the interfacial structure. Thickness of the interfacial phases was digitally measured and the activation energy was deduced for the growth of Cu₃Sn. Kirkendall voids formed at the Cu/Cu₃Sn interface as well as within the Cu₃Sn layer. The thickness of Cu₃Sn significantly increased with aging time, but that of Cu₆Sn₅ changed a little. The interfacial Cu₃Sn layer was found growing at the expense of Cu₆Sn₅. Evolution of the interfacial structure during thermal aging is discussed.     

Distance-Based Decision Fusion in a Distributed Wireless Sensor Network

Target classification fusion problem in a distributed, wireless sensor network is investigated. We propose a distance-based decision fusion scheme exploiting the relationship between sensor to target distance, signal to noise ratio and classification rate, which requires less communication while achieving higher region classification rate when compared to conventional majority-vote-based fusion schemes. Several different methods are tested, and very encouraging simulation results using real world experimental data samples are also observed.     

Adaptive decision feedback equalization: can you skip the trainingperiod?

This paper presents a novel unsupervised (blind) adaptive decision feedback equalizer (DFE). It can be thought of as the cascade of four devices, whose main components are a purely recursive filter (ℛ) and a transversal filter (𝒯). Its major feature is the ability to deal with severe quickly time-varying channels, unlike the conventional adaptive DFE. This result is obtained by allowing the new equalizer to modify, in a reversible way, both its structure and its adaptation according to some measure of performance such as the mean-square error (MSE). In the starting mode, ℛ comes first and whitens its own output by means of a prediction principle, while 𝒯 removes the remaining intersymbol interference (ISI) thanks to the Godard (1980) (or Shalvi-Weinstein (1990)) algorithm. In the tracking mode the equalizer becomes the classical DFE controlled by the decision-directed (DD) least-mean-square (LMS) algorithm. With the same computational complexity, the new unsupervised equalizer exhibits the same convergence speed, steady-state MSE, and bit-error rate (BER) as the trained conventional DFE, but it requires no training. It has been implemented on a digital signal processor (DSP) and tested on underwater communications signals-its performances are really convincing