Source-wavelet estimation during full-waveform inversion of ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole ground-penetrating radar (GPR) data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a recently published time-domain inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity of both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little to no trade-off between the wavelet estimation and the tomographic imaging procedures.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Effectiveness of Parallel Noise Barriers - An Iowa Study, HR-540, 1987

Traffic noise monitoring using FHWA's Demonstration Projects Division Mobile Noise Laboratory at free field, single wall and parallel barrier site on I-380 in Evansdale, Iowa is described. Access to I-380 prior to its being open to traffic afforded a controlled pass-by monitoring phase involving different vehicle types. A subsequent second phase entailed identical measurement methodology to monitor "real world" I-380 traffic noise. Phase I data indicated increases in noise were significant under the parallel barrier conditions for light duty vehicles operating in the far lane. Phase II results showed that the actual I-380 traffic mix largely offset the earlier observed effect, but minor increases in traffic noise under the parallel system were noted. These differences in noise barrier system effectiveness are judged to be insignificant at this particular study location.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Methods for the analysis of two dimensional measurement data of paper web

This work is devoted to the problem of reconstructing the basis weight structure at paper web with black{box techniques. The data that is analyzed comes from a real paper machine and is collected by an o®-line scanner. The principal mathematical tool used in this work is Autoregressive Moving Average (ARMA) modelling. When coupled with the Discrete Fourier Transform (DFT), it gives a very flexible and interesting tool for analyzing properties of the paper web. Both ARMA and DFT are independently used to represent the given signal in a simplified version of our algorithm, but the final goal is to combine the two together. Ljung-Box Q-statistic lack-of-fit test combined with the Root Mean Squared Error coefficient gives a tool to separate significant signals from noise.

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

Collecting Transaction Data in a Fourth Generation Mobile Network

Tässä diplomityössä on oletettu että neljännen sukupolven mobiiliverkko on saumaton yhdistelmä olemassa olevia toisen ja kolmannen sukupolven langattomia verkkoja sekä lyhyen kantaman WLAN- ja Bluetooth-radiotekniikoita. Näiden tekniikoiden on myös oletettu olevan niin yhteensopivia ettei käyttäjä havaitse saanti verkon muuttumista. Työ esittelee neljännen sukupolven mobiiliverkkoihin liittyvien tärkeimpien langattomien tekniikoiden arkkitehtuurin ja perustoiminta-periaatteet. Työ kuvaa eri tekniikoita ja käytäntöjä tiedon mittaamiseen ja keräämiseen. Saatuja transaktiomittauksia voidaan käyttää tarjottaessa erilaistettuja palvelutasoja sekä verkko- ja palvelukapasiteetin optimoimisessa. Lisäksi työssä esitellään Internet Business Information Manager joka on ohjelmistokehys hajautetun tiedon keräämiseen. Sen keräämää mittaustietoa voidaan käyttää palvelun tason seurannassa j a raportoinnissa sekä laskutuksessa. Työn käytännön osuudessa piti kehittää langattoman verkon liikennettä seuraava agentti joka tarkkailisi palvelun laatua. Agentti sijaitsisi matkapuhelimessa mitaten verkon liikennettä. Agenttia ei kuitenkaan voitu toteuttaa koska ohjelmistoympäristö todettiin vajaaksi. Joka tapauksessa työ osoitti että käyttäjän näkökulmasta tietoa kerääville agenteille on todellinen tarve.

All-sky search algorithms for monochromatic signals in bar gravitational wave detector data

In this paper we design and develop several filtering strategies for the analysis of data generated by a resonant bar gravitational wave (GW) antenna, with the goal of assessing the presence (or absence) therein of long-duration monochromatic GW signals, as well as the eventual amplitude and frequency of the signals, within the sensitivity band of the detector. Such signals are most likely generated in the fast rotation of slightly asymmetric spinning stars. We develop practical procedures, together with a study of their statistical properties, which will provide us with useful information on the performance of each technique. The selection of candidate events will then be established according to threshold-crossing probabilities, based on the Neyman-Pearson criterion. In particular, it will be shown that our approach, based on phase estimation, presents a better signal-to-noise ratio than does pure spectral analysis, the most common approach.

Bluetooth -teknologian hyödyntäminen kommunikointijärjestelmässä

Erilaisissa rakennuksissa on selkeä tarve langatonta teknologiaa hyödyntävälle, edulliselle ja monipuoliselle kommunikointijärjestelmälle, jota voidaan pienin muutoksin käyttää lähes missä tahansa. Kommunikointijärjestelmän avulla tulee olla mahdollista siirtää ääntä ja dataa sekä tarvittaessa tarjota erilaisia rakennuksissa tarvittavia palveluita. Tehdyn esitutkimuksen perusteella valittiin toteutusteknologiaksi Bluetooth, joka monipuolisten ominaisuuksien ja pienen sirukoon ansiosta soveltuu parhaiten tämän diplomityön mukaisen kerrostalon kommunikointijärjestelmän toteuttamiseen. Pieni sirukoko ja edullinen hinta mahdollistavat Bluetooth -teknologiaa hyödyntävän kommunikointijärjestelmän käyttöönoton myös vanhoissa kerrostaloissa. Pienet sirut on helppo piilottaa rakennusten perustuksiin ja mitään valmista verkkoinfrastruktuuria ei tarvita. OBEX (Object Exchange Protocol) -protokollaa käytetään tämän diplomityön mukaisessa Talovastaajapalvelussa audiodatan kuljettamiseen ja autentikointitietojen vaihtamiseen. Talovastaajapalvelu toteutettiin kommunikointijärjestelmän yhteyteen ja se toimii normaalin puhelinvastaajan tapaan, mutta on ominaisuuksiltaan paljon monipuolisempi ja käyttää langatonta Bluetooth -teknologiaa. OBEX:n avulla Talovastaajapalvelusta saatiin yksinkertainen, tehokas ja helposti laajennettavissa oleva kokonaisuus, jota voidaan käyttää pienin muutoksin lähes missä tahansa muussa Bluetooth -teknologiaa hyödyntävässä järjestelmässä.

Tolerance and Relative Utility: Two Proposed Indices for Comparing Change in Clinical Measurement Noise Between Different Populations (Repeatability) or Measurement Methods (Agreement).

Reaching a consensus in terms of interchangeability and utility (i.e., disease detection/monitoring) of a medical device is the eventual aim of repeatability and agreement studies. The aim of the tolerance and relative utility indices described in this report is to provide a methodology to compare change in clinical measurement noise between different populations (repeatability) or measurement methods (agreement), so as to highlight problematic areas. No longitudinal data are required to calculate these indices. Both indices establish a metric of least to most effected across all parameters to facilitate comparison. If validated, these indices may prove useful tools when combining reports and forming the consensus required in the validation process for software updates and new medical devices.

The role of Bluetooth technology in transforming the value network of ICT industry

Tutkimuksen tavoitteena oli selvittää miten Bluetooth-teknologia voi vaikuttaa ICT-alan arvoverkkoon ja alan toimijoiden rooleihin. Tutkimuksessa käytettiin kvalitatiivisia menetelmiä ja siinä oli piirteitä tulevaisuuden tutkimuksesta, koska myös eksploratiivisia menetelmiä käytettiin. Tutkimus perustui laajalti kirjallisuuteen ja artikkeleihin, joiden perusteella muodostettiin skenaarioita ICT-alan tulevaisuuden arvoverkosta. Tutkimus sisälsi myös empiirisen osion, jossa järjestettiin kaksi ryhmäkeskustelua, joissa alan toimijat keskustelivat muodostetuista skenaarioista sekä yleisemmin Bluetoothin vaikutuksista arvoverkkoon. Tutkimuksen mukaan ICT-alan arvoverkko tulevaisuudessa on rakenteeltaan strateginen arvoverkko, jota johtaa eri toimija erilaisissa markkinatilanteissa. Verkon strateginen keskus voi muuttua ajan kuluessa kun Bluetoothin sovelluskohteet lisääntyvät ja se voi vaihdella markkina-alueesta toiseen. Bluetooth luo uuden kommunikaatiokanavan nykyisten rinnalle ja se voi paikallisesti korvata nykyisten kanavien käytön tiedon siirrossa. Bluetooth voi synnyttää lukuisia uusia liiketoimintamahdollisuuksia ja sen avulla voidaan tuottaa lisäarvopalveluita. Suurimpien muutosten voidaan olettaa koskevan teleoperaattoreiden ja sisällöntuottajien liiketoimintaa.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Physiological noise in human cerebellar fMRI.

OBJECTIVES: To compare physiological noise contributions in cerebellar and cerebral regions of interest in high-resolution functional magnetic resonance imaging (fMRI) data acquired at 7T, to estimate the need for physiological noise removal in cerebellar fMRI. MATERIALS AND METHODS: Signal fluctuations in high resolution (1 mm isotropic) 7T fMRI data were attributed to one of the following categories: task-induced BOLD changes, slow drift, signal changes correlated with the cardiac and respiratory cycles, signal changes related to the cardiac rate and respiratory volume per unit of time or other. [Formula: see text] values for all categories were compared across regions of interest. RESULTS: In this high-resolution data, signal fluctuations related to the phase of the cardiac cycle and cardiac rate were shown to be significant, but comparable between cerebellar and cerebral regions of interest. However, respiratory related signal fluctuations were increased in the cerebellar regions, with explained variances that were up to 80 % higher than for the primary motor cortex region. CONCLUSION: Even at a millimetre spatial resolution, significant correlations with both cardiac and respiratory RETROICOR components were found in all healthy volunteer data. Therefore, physiological noise correction is highly likely to improve the temporal signal-to-noise ratio (SNR) for cerebellar fMRI at 7T, even at high spatial resolution.

Singling out individual inventors from patent data

An increasing number of studies in recent years have sought to identify individual inventors from patent data. A variety of heuristics have been proposed for using the names and other information disclosed in patent documents to establish who is who in patents. This paper contributes to this literature by describing a methodology for identifying inventors using patents applied to the European Patent Office, EPO hereafter. As in much of this literature, we basically follow a threestep procedure : 1- the parsing stage, aimed at reducing the noise in the inventor’s name and other fields of the patent; 2- the matching stage, where name matching algorithms are used to group similar names; and 3- the filtering stage, where additional information and various scoring schemes are used to filter out these similarlynamed inventors. The paper presents the results obtained by using the algorithms with the set of European inventors applying to the EPO over a long period of time.