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We report on the successful preparation of Fe-N codoped Titania powders, using TiO 2 Degussa P25, salt of Fe (II), and Urea. Modified Titania-based materials were characterized by SEM, EDS, BET, Raman, XRD diffraction and diffuse reflectance UV–vis spectroscopy measurements. The doping of TiO 2 induced a shift in the absorption threshold toward the spectral range, obtaining catalysts with a greater photoactivity than the one of pure Degussa P25. The degradation of 200 mL of a solution with 50 mg L − 1 acid blue BR dye in sulfate medium at pH 3.0 has been comparatively studied by electrochemical oxidation using a boron doped diamond anode (EO-BDD), Photocatalysis TiO 2 -Fe-N, and coupled material of EO-BDD/Photocatalysis TiO 2 -Fe-N. The solution was slowly degraded by EO-BDD (25%) and single Photocatalysis TiO 2 -Fe-N because of the low rate of dye degradation and its colored by-products with hydroxyl radicals generated at the BDD anode and catalyst surface from water oxidation (29%), whereas the solution was more rapidly degraded using coupled material of EO-BDD/Photocatalysis TiO 2 -Fe-N (82%), owing to the additional generation of hydroxyl radicals from the photocatalysis of TiO 2 -Fe-N and BDD anode. [ABSTRACT FROM AUTHOR]

This work reports the comparative performance of two Advanced Oxidation Processes (AOPs), electrochemical oxidation and photocatalysis, as individual technological alternatives for the treatment of effluents containing p-cresol. First, the influence of operating parameters in the oxidation and mineralization yield was carried out together with kinetic analysis. Boron Doped Diamond (BDD), RuO 2 and Pt as anodic materials, Na 2 SO 4 and NaCl as supporting electrolytes and different current densities were evaluated in electrochemical oxidation whereas the effect of TiO 2 concentration and radiation was studied in the photocatalytic degradation. Then, the parameter Electrical Energy per Order (E EO ) was calculated to compare the energy consumption in both AOPs, concluding that under the studied conditions the electrochemical treatment with BDD, Na 2 SO 4 and 125 A m −2 showed the best energy efficiency, with an E EO of 5.83 kW h m −3 order −1 for p-cresol and 58.05 kW h m −3 order −1 for DOC removal, respectively. [ABSTRACT FROM AUTHOR]

In multicarrier code-division multiple access systems the linear distortion introduced by the channel causes a perturbation in the received user codes that produces multiple access interference. This paper introduces two new techniques to combat this distortion that are based on subspace decomposition. The first one consists of obtaining an approximation of the received desired user code to improve the output signal to interference noise ratio in blind linear receivers. This approximation is obtained by means of the projection of the known transmitted desired user code onto the signal subspace. The second one is a blind channel estimation method that uses the orthogonality property between the received user codes and the noise subspace. We demonstrate that the performance of channel estimation methods based on this property are severely limited by the number of simultaneous users. Nevertheless, it is shown how this limitation is overcome if user codes spanning several transmitted symbols (long codes) are used. [Copyright &y& Elsevier]

Explores the problem of blind channel identification for direct-sequence/code-division multiple-access multiuser systems. Signal model; Toeplitz displacement-based channel estimation; Approximation of mean-squared estimation error.

Provides information on a study which presented a modified constant modulus algorithm (CMA) equalizer for the removal of length dependent local minima in autoregressive channels. Statement of the problem; Modification of CMA; Conclusions.

Proposes an approach based on the constant modulus (CM) criterion to separate instantaneous linear mixtures of signals using a linear memoryless multiple input multiple output (MIMO) system. Constant modulus analysis-based optimization criterion; Analysis of stationary points of the proposed cost function; Results of the computer simulations of the proposed method; Conclusions.

Indoor positioning systems based on radio frequency inherently present multipath-related phenomena. This causes ranging systems such as ultra-wideband (UWB) to lose accuracy when detecting secondary propagation paths between two devices. If a positioning algorithm uses ranging measurements without considering these phenomena, it will face critical errors in estimating the position. This work analyzes the performance obtained in a localization system when combining location algorithms with machine learning techniques applied to a previous classification and mitigation of the propagation effects. For this purpose, real-world cross-scenarios are considered, where the data extracted from low-cost UWB devices for training the algorithms come from a scenario different from that considered for the test. The experimental results reveal that machine learning (ML) techniques are suitable for detecting non-line-of-sight (NLOS) ranging values in this situation. [ABSTRACT FROM AUTHOR]

Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters. In this work, machine learning (ML) techniques are employed to analyze several sets of real UWB measurements, captured in different scenarios, to try to identify the measurements facing non-line-of-sight (NLOS) propagation condition. Additionally, an ulterior process is carried out to mitigate the deviation of these measurements from the actual distance value between the devices. The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver. [ABSTRACT FROM AUTHOR]

The rising popularity of location-based services has prompted considerable research in the field of indoor location systems. Since there is no single technology to support these systems, it is necessary to consider the fusion of the information coming from heterogeneous sensors. This paper presents a software architecture designed for a hybrid location system where we can merge information from multiple sensor technologies. The architecture was designed to be used by different kinds of actors independently and with mutual transparency: hardware administrators, algorithm developers and user applications. The paper presents the architecture design, work-flow, case study examples and some results to show how different technologies can be exploited to obtain a good estimation of a target position. [ABSTRACT FROM AUTHOR]

In professional audio production the setup of electronic musical devices is a time-consuming and error-prone process, as it involves manual operations like establishing local configurations and carrying cables for each device. Such is the case of MIDI (musical instrument digital interface), which is widely used in the context of musical applications. On the other hand, the capabilities of WSN (wireless sensor networks) allow developers to build up more complex applications, since nodes have the ability of auto identifying, auto configuring, and establishing associations with other nodes, behaving in a smarter way than other networks. In this paper, we propose the use of an optimized WSN network for interconnecting MIDI devices. This network has been named collaborative musical wireless network (CMWN): it eases device configuration, enables musical collaboration, and allows artists to explore new ways of expression. The paper also presents the hardware and performance results of a prototype able to create CMWNs. [ABSTRACT FROM AUTHOR]

This article presents a Virtual Transducer Electronic Data Sheet (VTEDS)-based framework for the development of intelligent sensor nodes with plug-and-play capabilities in order to contribute to the evolution of the Internet of Things (IoT) toward the Web of Things (WoT). It makes use of new lightweight protocols that allow sensors to self-describe, auto-calibrate, and auto-register. Such protocols enable the development of novel IoT solutions while guaranteeing low latency, low power consumption, and the required Quality of Service (QoS). Thanks to the developed human-centered tools, it is possible to configure and modify dynamically IoT device firmware, managing the active transducers and their communication protocols in an easy and intuitive way, without requiring any prior programming knowledge. In order to evaluate the performance of the system, it was tested when using Bluetooth Low Energy (BLE) and Ethernet-based smart sensors in different scenarios. Specifically, user experience was quantified empirically (i.e., how fast the system shows collected data to a user was measured). The obtained results show that the proposed VTED architecture is very fast, with some smart sensors (located in Europe) able to self-register and self-configure in a remote cloud (in South America) in less than 3 s and to display data to remote users in less than 2 s. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) involves a wide variety of heterogeneous technologies and resource-constrained devices that interact with each other. Due to such constraints, IoT devices usually require lightweight protocols that optimize the use of resources and energy consumption. Among the different commercial IoT devices, Bluetooth and Bluetooth Low Energy (BLE)-based beacons, which broadcast periodically certain data packets to notify their presence, have experienced a remarkable growth, specially due to their application in indoor positioning systems. This article proposes a family of protocols named Lightweight Protocol for Sensors (LP4S) that provides fast responses and enables plug-and-play mechanisms that allow IoT telemetry systems to discover new nodes and to describe and auto-register the sensors and actuators connected to a beacon. Thus, three protocols are defined depending on the beacon hardware characteristics: LP4S-6 (for resource-constraint beacons), LP4S-X (for more powerful beacons) and LP4S-J (for beacons able to run complex firmware). In order to demonstrate the capabilities of the designed protocols, the most restrictive (LP4S-6) is tested after implementing it for a telemetry application in a beacon based on Eddystone (Google's open beacon format). Thus, the beacon specification is extended in order to increase its ability to manage unlimited sensors in a telemetry system without interfering in its normal operation with Eddystone frames. The performed experiments show the feasibility of the proposed solution and its superiority, in terms of latency and energy consumption, with respect to approaches based on Generic Attribute Profile (GATT) when multiple users connect to a mote or in scenarios where latency is not a restriction, but where low-energy consumption is essential. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we address the problem of indoor tracking using received signal strength (RSS) as a position-dependent data measurement. Since RSS is highly influenced by multipath propagation, it turns out very hard to adequately model the correspondence between the received power and the transmitter-to-receiver distance. Although various models have been proposed in the literature, they often require the use of very large collections of data in order to fit them and display great sensitivity to changes in the radio propagation environment. In this work we advocate the use of switching multiple models that account for different classes of target dynamics and propagation environments and propose a flexible probabilistic switching scheme. The resulting state-space structure is termed a generalized switching multiple model (GSMM) system. Within this framework, we investigate two types of models for the RSS data: polynomial models and classical logarithmic path-loss representation. The first model is more accurate however it demands an offline model fitting step. The second one is less precise but it can be fitted in an online procedure. We have designed two tracking algorithms built around a Rao-Blackwellized particle filter, tailored to the GSMM structure and assessed its performances both with synthetic and experimental measurements. [Copyright &y& Elsevier]

Presents abstracts of various manuscripts regarding signal processing. A family of algorithms for fast approximate subspace tracking; Ladder realization of biorthogonal multiband filter banks; A general weighted median filter structure admitting real-valued weights.