4,651 research outputs found
AoA-aware Probabilistic Indoor Location Fingerprinting using Channel State Information
With expeditious development of wireless communications, location
fingerprinting (LF) has nurtured considerable indoor location based services
(ILBSs) in the field of Internet of Things (IoT). For most pattern-matching
based LF solutions, previous works either appeal to the simple received signal
strength (RSS), which suffers from dramatic performance degradation due to
sophisticated environmental dynamics, or rely on the fine-grained physical
layer channel state information (CSI), whose intricate structure leads to an
increased computational complexity. Meanwhile, the harsh indoor environment can
also breed similar radio signatures among certain predefined reference points
(RPs), which may be randomly distributed in the area of interest, thus mightily
tampering the location mapping accuracy. To work out these dilemmas, during the
offline site survey, we first adopt autoregressive (AR) modeling entropy of CSI
amplitude as location fingerprint, which shares the structural simplicity of
RSS while reserving the most location-specific statistical channel information.
Moreover, an additional angle of arrival (AoA) fingerprint can be accurately
retrieved from CSI phase through an enhanced subspace based algorithm, which
serves to further eliminate the error-prone RP candidates. In the online phase,
by exploiting both CSI amplitude and phase information, a novel bivariate
kernel regression scheme is proposed to precisely infer the target's location.
Results from extensive indoor experiments validate the superior localization
performance of our proposed system over previous approaches
Remote sensing of snow using bistatic radar reflectometry
Snow and ice processes are a critical part of the Earth’s hydrological and climate cycles. These processes can serve as an important source of fresh water as well as a cause of flooding. Various missions have been proposed by NASA and ESA for the purpose of remote sensing of snow. This research looks at applying bistatic radar reflectometry to the remote sensing of snow water equivalent. The resulting phase offset from changes in optical path length due to reflection through snow are the primary measurements made. The research uses data from a field campaign in Fraser, CO, involving an instrument collecting direct and reflected from S band during Jan 2015 – Apr 2015. Phase measurements from the field data are made from the two signals and compared to theoretical phase computed from a forward model using in situ data. A moderate correlation (\u3e0.6) is found between the measured and modeled phase
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Integrated impedance spectroscopy biosensors
textAffinity-based biosensors, or in short biosensors, are extremely powerful and versatile analytical tools which are used for the detection of a wide variety of bio-molecules. In recent times, there has been a need for developing low-cost and portable affinity-based biosensor platforms. Such systems need to have a high density of detection sites (i.e biosensing elements) in order to simultaneously detect multiple analytes in a single sample. This has led to the creation of integrated biosensors, which make use of integrated circuits (ICs) for bio-molecular detection. In such systems, it has been demonstrated that by taking advantage of the capabilities of semiconductor and very large scale integrated (VLSI) circuit fabrication processes, it is possible to build compact miniaturized biosensors, which can be used in wide variety of applications such as in molecular diagnostics and for environmental monitoring.
Among the various detection modalities for biosensors, Electrochemical Impedance Spectroscopy (EIS) permits real-time detection and has label-free detection capabilities. EIS is fully electronic in nature. Hence, it can be implemented using standard IC technologies. The versatility and ease of integration of EIS makes it a promising candidate for developing integrated biosensor platforms.
In this thesis, we first examine the underlying principles of EIS method of biosensing. By analyzing an immunosensor assay as an example, we show that EIS based biosensing is a highly sensitive detection method, which can be used for the detection of a wide variety of analytes. Since EIS relies on small impedance changes in order to perform detection, it requires highly accurate models for the electrode-electrolyte systems. Hence, we also introduce a compact modeling technique for the distributed electrode-electrolyte systems with non-uniform electric fields, which is capable of modelling noise and other non-idealities in EIS.
In the second part of this thesis, we describe the design and implementation of an integrated EIS biosensor array, built using a standard complementary metal-oxide-semiconductor (CMOS) process. The chip is capable of measuring admittance values as small as 10nS and has a wide dynamic range (90dB) over a wide range of frequencies (10Hz-50MHz). We also report the results obtained from the DNA and protein detection experiments performed using this chip.Electrical and Computer Engineerin
Training-to-Beat bioreactor for investigating Engineered Cardiac Tissues: design, development & validation
In last the decades, advances relevant to the generation of 3D Engineered Cardiac Tissues (ECTs) have been made. In reason of this, ECTs are now considered a great promise for in vitro studies of cardiac development, disease and, eventually, for strategies for the repair of the structure and function of the injured myocardium.
Among the several physical stimuli which have been exploited to improve the functionality and maturation of ECTs, a preeminent role has been ascribed to mechanical stimulation. Appropriate mechanical stimulation can be recreated and maintained within bioreactors, which are devices/platforms devoted to mimic the physiological milieu in a monitored/controlled culture environment, where the engineered constructs can be properly stimulated.
One main limitation of the bioreactor-based strategy for cardiac tissue engineering applications is that the devices which are currently used are meant to passively apply to ECTs a stimulus predefined by the user, regardless of their level of maturation along the duration of the in vitro culture.
In this scenario, and trying to overcome current limitations, a novel bioreactor design has been conceived for the investigation of 3D ECTs with a biomimetic approach. Technically, the here proposed bioreactor is capable (1) to apply native-like or pathologic mechanical stimuli (cyclic strain) by means of a reliable linear actuator operating in a wide range of strains and frequencies, and (2) to monitor in real-time both chemo-physical parameters (e.g. oxygen tension, pH) of the milieu and the mechanical stiffness of ECTs by means of dedicated sensors, eventually adapting the stimulation to the actual stage of maturation of the constructs.
As a proof of concept, a first experimental campaign has been carried out with a double aim: (1) to verify the bioreactor feasibility in delivering mechanical cyclical stimulation to 3D fibrin-based, ring shaped Engineered Cardiac Tissues (ECTs); (2) to assess the effect of cyclic strain on tissue maturation, contractility and modification on its mechanical properties.
In detail, the bioreactor platform has been preliminarily tested to verify protocols for hold on, sterilization, and control of the delivered mechanical stimuli. Firstly, the suitability of the bioreactor platform in culturing ad-hoc designed constructs, in terms of ease of use and capability in setting the stimulation parameters, has been tested. Then, the observed maturation of ring shaped ECTs subject to sinusoidal cyclic strain within the bioreactor has confirmed the potency of the proposed approach and the instrumental role of mechanical stimulation in ECTs maturation and in the development of an adult-like cardiac phenotype responsive to electrical excitation.
Even if further validation steps are required before the implementation of culture strategy fully adaptive in terms of mechanical stimuli applied to the engineered cardiac constructs, the developed bioreactor represents a valuable proof of concept for, in its most advanced operational mode, biomimetic culturing of engineered cardiac constructs
Seeing the Invisibles:Detection of Peptide Enantiomers, Diastereomers, and Isobaric Ring Formation in Lanthipeptides Using Nanopores
Mass spectrometry (MS) is widely used in proteomic analysis but cannot differentiate between molecules with the same mass-to-charge ratio. Nanopore technology might provide an alternative method for the rapid and cost-effective analysis and sequencing of proteins. In this study, we demonstrate that nanopore currents can distinguish between diastereomeric and enantiomeric differences in l- and d-peptides, not observed by conventional MS analysis, down to individual d-amino acids in small opioid peptides. Molecular dynamics simulations suggest that similar to chiral chromatography the resolution likely arises from multiple chiral interactions during peptide transport across the nanopore. Additionally, we used nanopore recordings to rapidly assess 4- and 11-amino acid ring formation in lanthipeptides, a process used in the synthesis of pharmaceutical peptides. The cyclization step requires distinguishing between constitutional isomers, which have identical MS signals and typically involve numerous tedious experiments to confirm. Hence, nanopore technology offers new possibilities for the rapid and cost-effective analysis of peptides, including those that cannot be easily differentiated by mass spectrometry.</p
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Space-time-frequency methods for interference-limited communication systems
textTraditionally, noise in communication systems has been modeled as an additive, white Gaussian noise process with independent, identically distributed samples. Although this model accurately reflects thermal noise present in communication system electronics, it fails to capture the statistics of interference and other sources of noise, e.g. in unlicensed communication bands. Modern communication system designers must take into account interference and non-Gaussian noise to maximize efficiencies and capacities of current and future communication networks. In this work, I develop new multi-dimensional signal processing methods to improve performance of communication systems in three applications areas: (i) underwater acoustic, (ii) powerline, and (iii) multi-antenna cellular. In underwater acoustic communications, I address impairments caused by strong, time-varying and Doppler-spread reverberations (self-interference) using adaptive space-time signal processing methods. I apply these methods to array receivers with a large number of elements. In powerline communications, I address impairments caused by non-Gaussian noise arising from devices sharing the powerline. I develop and apply a cyclic adaptive modulation and coding scheme and a factor-graph-based impulsive noise mitigation method to improve signal quality and boost link throughput and robustness. In cellular communications, I develop a low-latency, high-throughput space-time-frequency processing framework used for large scale (up to 128 antenna) MIMO. This framework is used in the world's first 100-antenna MIMO system and processes up to 492 Gbps raw baseband samples in the uplink and downlink directions. My methods prove that multi-dimensional processing methods can be applied to increase communication system performance without sacrificing real-time requirements.Electrical and Computer Engineerin
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The Evaluation of Multichannel Shortwave Infrared (SWIR) Optical Data from the Japanese Earth Resources Satellite (JERS-1), for Geological Applications
The primary objective of this thesis is to evaluate data from the Japanese Earth Resources Satellite (JERS-1), particularly multi-channel shortwave infrared (SWIR) data. These data are to be evaluated in comparison with Landsat Thematic Mapper (TM) data for geological applications, in particular lithological discrimination in an arid environment (Oman) and volcano monitoring (Lascar, Chile).
JERS-1 is the first satellite purposely designed for geological remote sensing. Optical data (OPS) acquired by JERS-1 is of a higher spatial and spectral resolution than that from-Landsat TM. Unfortunately the immediate benefits of this higher resolution are lost due to the low quality of all OPS data. All seven OPS channels are affected by along- and across-track striping, image blur at spectral boundaries, poor dynamic
ranges, random speckle and inter-channel misregistration. Poor data quality greatly reduces the geological potential of these data, especially as the most severely corrupted channels are OPS 6 and OPS 7, two of the new narrow SWIR channels. However, despite poor data quality the majority of the noise artefacts associated with these data can be either removed or significantly reduced by processing in the frequency domain. A number of frequency domain techmques have been developed which separate noise features from real image data. These techniques greatly improve the quality of most OPS channels, although OPS 6 and OPS 7 are sometimes beyond recovery.
The spectral characteristics of the lithologies comprising the Oman ophiolite complex are used to demonstrate the increased discrimination potential of ‘cleaned’ multichannel OPS data. High resolution lab spectra of the ophiolite lithologies were degraded to TM and OPS spectral resolutions in order to determine the influence of spectral resolution on lithologie discrimination. The results of this comparison indicated that a lot of discrimination information seen at lab resolution is lost at OPS and TM resolution. This results in the reflectance spectra of some ophiolite lithologies appearing very similar, especially at TM resolution. More discrimination information is preserved at OPS resolution due to the sub-division of the wavelength range equivalent to TM 7 into three narrow discrete channels. Analysis of resampled spectra at OPS resolution shows that OPS 8 conrtbutes new spectral information not discernible at TM resolution.
Resampled lab spectra at OPS resolution were used to try to develop effective band combinations and image processing techniques capable of discriminating ophiolite lithologies. Tests of OPS band composites indicated that the best composite was one which combined three bands from spectrally distinct parts of the spectrum. OPS 852 proved to be the most effective OPS composite, discriminating the majority of ophilite lithologies. Analysis of both spectral and image data showed that OPS 6 and OPS 7 are highly correlated for ophiolite lithologies. Composites combining both of these channels were very poor, however combining one channel (usually OPS 6 due to quality) with OPS 8 and OPS 2 produced a reasonable composite (OPS 862). OPS 852 is the most informative composite, and would remain so even if OPS 6 and OPS 7 were of a higher quality. Comparisons with the best TM composite (TM 754 decorrelation stretched) showed that the OPS data discriminated more lithologies and often allowed previously mapped units to be sub-divided.
To test the potential of OPS data for volcano monitoring a time series of four OPS scenes, straddling the April 1993 eruption of Lascar (Chile), were analysed. This study showed that the higher spatial resolution of the OPS sensor was capable of detecting smaller thermal features than possible with TM. This resulted in four intra-crater maps of thermal anomolies being produced, showing thermal variations associated with periods of dome growth and collapse. These data also demonstrated their usefulness for mapping the extent of pyroclastic deposits emplaced during this eruption, and also their subsequent rapid erosion.
Overall OPS data are shown to offer significant improvements with respect to lithological mapping and volcano monitoring despite their greatly reduced quality compared with Landsat TM. Extensive tests of various band combinations and processing techniques show that some of the most informative images derived of the ophiolite lithologies consist simply of cleaned channels of data combined as false colour composites. The effectiveness and possible advantages of advanced image processing techniques are often negligible due to the rapid degradation of the data when subjected to intensive processing. OPS 8 is the channel mainly responsible for contributing additional new valuable spectral information, that is not available from Landsat TM. The slight increases in spatial and spectral resolution offered by OPS data result in significantly more geological information being discernible from an OPS composite than on the equivalent TM composite
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