On-Body Channel Measurement Using Wireless Sensors

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.This post-acceptance version of the paper is essentially complete, but may differ from the official copy of record, which can be found at the following web location (subscription required to access full paper): http://dx.doi.org/10.1109/TAP.2012.219693

Simulating halocarbon concentrations in ocean and atmosphere from industrial water treatment

Large volumes of seawater are used in different industrial sectors such as power plants and ships. Chemical disinfection of this seawater prevents bio-fouling, but also produces halogenated disinfection by-products (DBPs). One major DBP is bromoform whose anthropogenic input to the environment is highly uncertain. Halocarbons such as bromoform impact the oxidation of trace gases and ozone chemistry in the atmosphere. We quantify the contribution of DBPs from industrial waste water to oceanic halocarbon concentrations and their impact on atmospheric chemistry. Based on industrial water discharge and DBP estimates, we simulate oceanic pathways of halocarbons along NEMO-ORCA12 driven Lagrangian trajectories. Anthropogenic halocarbon concentration are strongly enhanced along the coasts in Southeast Asia, but also allow for transport into the open ocean. We highlight bromoform showing that its anthropogenic sources can explain much of observed shelf water concentrations. We show how anthropogenic marine bromine impacts tropospheric and stratospheric ozone chemistry compared to natural background emissions

Presentations eBook: according to 1st Workshop with focus on experimental testing of cement-based materials

COST TU 140

40th Rocky Mountain Conference on Analytical Chemistry

Final program, abstracts, and information about the 40th annual meeting of the Rocky Mountain Conference on Analytical Chemistry, co-sponsored by the Colorado Section of the American Chemical Society and the Rocky Mountain Section of the Society for Applied Spectroscopy. Held in Denver, Colorado, July 25 - August 1, 1998

Acoustic modelling, data augmentation and feature extraction for in-pipe machine learning applications

Gathering measurements from infrastructure, private premises, and harsh environments can be difficult and expensive. From this perspective, the development of new machine learning algorithms is strongly affected by the availability of training and test data. We focus on audio archives for in-pipe events. Although several examples of pipe-related applications can be found in the literature, datasets of audio/vibration recordings are much scarcer, and the only references found relate to leakage detection and characterisation. Therefore, this work proposes a methodology to relieve the burden of data collection for acoustic events in deployed pipes. The aim is to maximise the yield of small sets of real recordings and demonstrate how to extract effective features for machine learning. The methodology developed requires the preliminary creation of a soundbank of audio samples gathered with simple weak annotations. For practical reasons, the case study is given by a range of appliances, fittings, and fixtures connected to pipes in domestic environments. The source recordings are low-reverberated audio signals enhanced through a bespoke spectral filter and containing the desired audio fingerprints. The soundbank is then processed to create an arbitrary number of synthetic augmented observations. The data augmentation improves the quality and the quantity of the metadata and automatically creates strong and accurate annotations that are both machine and human-readable. Besides, the implemented processing chain allows precise control of properties such as signal-to-noise ratio, duration of the events, and the number of overlapping events. The inter-class variability is expanded by recombining source audio blocks and adding simulated artificial reverberation obtained through an acoustic model developed for the purpose. Finally, the dataset is synthesised to guarantee separability and balance. A few signal representations are optimised to maximise the classification performance, and the results are reported as a benchmark for future developments. The contribution to the existing knowledge concerns several aspects of the processing chain implemented. A novel quasi-analytic acoustic model is introduced to simulate in-pipe reverberations, adopting a three-layer architecture particularly convenient for batch processing. The first layer includes two algorithms: one for the numerical calculation of the axial wavenumbers and one for the separation of the modes. The latter, in particular, provides a workaround for a problem not explicitly treated in the literature and related to the modal non-orthogonality given by the solid-liquid interface in the analysed domain. A set of results for different waveguides is reported to compare the dispersive behaviour against different mechanical configurations. Two more novel solutions are also included in the second layer of the model and concern the integration of the acoustic sources. Specifically, the amplitudes of the non-orthogonal modal potentials are obtained using either a distance minimisation objective function or by solving an analytical decoupling problem. In both cases, results show that sources sufficiently smooth can be approximated with a limited number of modes keeping the error below 1%. The last layer proposes a bespoke approach for the integration of the acoustic model into the synthesiser as a reverberation simulator. Additional elements of novelty relate to the other blocks of the audio synthesiser. The statistical spectral filter, for instance, is a batch-processing solution for the attenuation of the background noise of the source recordings. The signal-to-noise ratio analysis for both moderate and high noise levels indicates a clear improvement of several decibels against the closest filter example in the literature. The recombination of the audio blocks and the system of fully tracked annotations are also novel extensions of similar approaches recently adopted in other contexts. Moreover, a bespoke synthesis strategy is proposed to guarantee separable and balanced datasets. The last contribution concerns the extraction of convenient sets of audio features. Elements of novelty are introduced for the optimisation of the filter banks of the mel-frequency cepstral coefficients and the scattering wavelet transform. In particular, compared to the respective standard definitions, the average F-score performance of the optimised features is roughly 6% higher in the first case and 2.5% higher for the latter. Finally, the soundbank, the synthetic dataset, and the fundamental blocks of the software library developed are publicly available for further research

58th Annual Rocky Mountain Conference on Magnetic Resonance

Final program, abstracts, and information about the 58th annual meeting of the Rocky Mountain Conference on Magnetic Resonance, co-endorsed by the Colorado Section of the American Chemical Society and the Society for Applied Spectroscopy. Held in Breckenridge, Colorado, July 17-21, 2016

Designing Sustainable Technologies, Products and Policies

This open access book provides insight into the implementation of Life Cycle approaches along the entire business value chain, supporting environmental, social and economic sustainability related to the development of industrial technologies, products, services and policies; and the development and management of smart agricultural systems, smart mobility systems, urban infrastructures and energy for the built environment. The book is based on papers presented at the 8th International Life Cycle Management Conference that took place from September 3-6, 2017 in Luxembourg, and which was organized by the Luxembourg Institute of Science and Technology (LIST) and the University of Luxembourg in the framework of the LCM Conference Series.