Large volume metrology process model:measurability analysis with integration of metrology classification model and feature-based selection model

Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.

A long non-coding RNA targets microRNA miR-34a to regulate colon cancer stem cell asymmetric division.

The roles of long non-coding RNAs (lncRNAs) in regulating cancer and stem cells are being increasingly appreciated. Its diverse mechanisms provide the regulatory network with a bigger repertoire to increase complexity. Here we report a novel LncRNA, Lnc34a, that is enriched in colon cancer stem cells (CCSCs) and initiates asymmetric division by directly targeting the microRNA miR-34a to cause its spatial imbalance. Lnc34a recruits Dnmt3a via PHB2 and HDAC1 to methylate and deacetylate the miR-34a promoter simultaneously, hence epigenetically silencing miR-34a expression independent of its upstream regulator, p53. Lnc34a levels affect CCSC self-renewal and colorectal cancer (CRC) growth in xenograft models. Lnc34a is upregulated in late-stage CRCs, contributing to epigenetic miR-34a silencing and CRC proliferation. The fact that lncRNA targets microRNA highlights the regulatory complexity of non-coding RNAs (ncRNAs), which occupy the bulk of the genome.

Coding Strategies and Implementations of Compressive Sensing

This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others.

This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system.

Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity.

Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

Temporal Coding of Volumetric Imagery

'Image volumes' refer to realizations of images in other dimensions such as time, spectrum, and focus. Recent advances in scientific, medical, and consumer applications demand improvements in image volume capture. Though image volume acquisition continues to advance, it maintains the same sampling mechanisms that have been used for decades; every voxel must be scanned and is presumed independent of its neighbors. Under these conditions, improving performance comes at the cost of increased system complexity, data rates, and power consumption.

This dissertation explores systems and methods capable of efficiently improving sensitivity and performance for image volume cameras, and specifically proposes several sampling strategies that utilize temporal coding to improve imaging system performance and enhance our awareness for a variety of dynamic applications.

Video cameras and camcorders sample the video volume (x,y,t) at fixed intervals to gain understanding of the volume's temporal evolution. Conventionally, one must reduce the spatial resolution to increase the framerate of such cameras. Using temporal coding via physical translation of an optical element known as a coded aperture, the compressive temporal imaging (CACTI) camera emonstrates a method which which to embed the temporal dimension of the video volume into spatial (x,y) measurements, thereby greatly improving temporal resolution with minimal loss of spatial resolution. This technique, which is among a family of compressive sampling strategies developed at Duke University, temporally codes the exposure readout functions at the pixel level.

Since video cameras nominally integrate the remaining image volume dimensions (e.g. spectrum and focus) at capture time, spectral (x,y,t,\lambda) and focal (x,y,t,z) image volumes are traditionally captured via sequential changes to the spectral and focal state of the system, respectively. The CACTI camera's ability to embed video volumes into images leads to exploration of other information within that video; namely, focal and spectral information. The next part of the thesis demonstrates derivative works of CACTI: compressive extended depth of field and compressive spectral-temporal imaging. These works successfully show the technique's extension of temporal coding to improve sensing performance in these other dimensions.

Geometrical optics-related tradeoffs, such as the classic challenges of wide-field-of-view and high resolution photography, have motivated the development of mulitscale camera arrays. The advent of such designs less than a decade ago heralds a new era of research- and engineering-related challenges. One significant challenge is that of managing the focal volume (x,y,z) over wide fields of view and resolutions. The fourth chapter shows advances on focus and image quality assessment for a class of multiscale gigapixel cameras developed at Duke.

Along the same line of work, we have explored methods for dynamic and adaptive addressing of focus via point spread function engineering. We demonstrate another form of temporal coding in the form of physical translation of the image plane from its nominal focal position. We demonstrate this technique's capability to generate arbitrary point spread functions.

A Binaural Cochlear Implant Sound Coding Strategy Inspired by the Contralateral Medial Olivocochlear Reflex.

OBJECTIVES: In natural hearing, cochlear mechanical compression is dynamically adjusted via the efferent medial olivocochlear reflex (MOCR). These adjustments probably help understanding speech in noisy environments and are not available to the users of current cochlear implants (CIs). The aims of the present study are to: (1) present a binaural CI sound processing strategy inspired by the control of cochlear compression provided by the contralateral MOCR in natural hearing; and (2) assess the benefits of the new strategy for understanding speech presented in competition with steady noise with a speech-like spectrum in various spatial configurations of the speech and noise sources. DESIGN: Pairs of CI sound processors (one per ear) were constructed to mimic or not mimic the effects of the contralateral MOCR on compression. For the nonmimicking condition (standard strategy or STD), the two processors in a pair functioned similarly to standard clinical processors (i.e., with fixed back-end compression and independently of each other). When configured to mimic the effects of the MOCR (MOC strategy), the two processors communicated with each other and the amount of back-end compression in a given frequency channel of each processor in the pair decreased/increased dynamically (so that output levels dropped/increased) with increases/decreases in the output energy from the corresponding frequency channel in the contralateral processor. Speech reception thresholds in speech-shaped noise were measured for 3 bilateral CI users and 2 single-sided deaf unilateral CI users. Thresholds were compared for the STD and MOC strategies in unilateral and bilateral listening conditions and for three spatial configurations of the speech and noise sources in simulated free-field conditions: speech and noise sources colocated in front of the listener, speech on the left ear with noise in front of the listener, and speech on the left ear with noise on the right ear. In both bilateral and unilateral listening, the electrical stimulus delivered to the test ear(s) was always calculated as if the listeners were wearing bilateral processors. RESULTS: In both unilateral and bilateral listening conditions, mean speech reception thresholds were comparable with the two strategies for colocated speech and noise sources, but were at least 2 dB lower (better) with the MOC than with the STD strategy for spatially separated speech and noise sources. In unilateral listening conditions, mean thresholds improved with increasing the spatial separation between the speech and noise sources regardless of the strategy but the improvement was significantly greater with the MOC strategy. In bilateral listening conditions, thresholds improved significantly with increasing the speech-noise spatial separation only with the MOC strategy. CONCLUSIONS: The MOC strategy (1) significantly improved the intelligibility of speech presented in competition with a spatially separated noise source, both in unilateral and bilateral listening conditions; (2) produced significant spatial release from masking in bilateral listening conditions, something that did not occur with fixed compression; and (3) enhanced spatial release from masking in unilateral listening conditions. The MOC strategy as implemented here, or a modified version of it, may be usefully applied in CIs and in hearing aids.

Formation of sub-7 nm feature size PS-b-P4VP block copolymer structures by solvent vapour process

The nanometer range structure produced by thin films of diblock copolymers makes them a great of interest as templates for the microelectronics industry. We investigated the effect of annealing solvents and/or mixture of the solvents in case of symmetric Poly (styrene-block-4vinylpyridine) (PS-b-P4VP) diblock copolymer to get the desired line patterns. In this paper, we used different molecular weights PS-b-P4VP to demonstrate the scalability of such high χ BCP system which requires precise fine-tuning of interfacial energies achieved by surface treatment and that improves the wetting property, ordering, and minimizes defect densities. Bare Silicon Substrates were also modified with polystyrene brush and ethylene glycol self-assembled monolayer in a simple quick reproducible way. Also, a novel and simple in situ hard mask technique was used to generate sub-7nm Iron oxide nanowires with a high aspect ratio on Silicon substrate, which can be used to develop silicon nanowires post pattern transfer.

Using Coding to Improve Localization and Backscatter Communication Performance in Low-Power Sensor Networks

Backscatter communication is an emerging wireless technology that recently has gained an increase in attention from both academic and industry circles. The key innovation of the technology is the ability of ultra-low power devices to utilize nearby existing radio signals to communicate. As there is no need to generate their own energetic radio signal, the devices can benefit from a simple design, are very inexpensive and are extremely energy efficient compared with traditional wireless communication. These benefits have made backscatter communication a desirable candidate for distributed wireless sensor network applications with energy constraints.

The backscatter channel presents a unique set of challenges. Unlike a conventional one-way communication (in which the information source is also the energy source), the backscatter channel experiences strong self-interference and spread Doppler clutter that mask the information-bearing (modulated) signal scattered from the device. Both of these sources of interference arise from the scattering of the transmitted signal off of objects, both stationary and moving, in the environment. Additionally, the measurement of the location of the backscatter device is negatively affected by both the clutter and the modulation of the signal return.

This work proposes a channel coding framework for the backscatter channel consisting of a bi-static transmitter/receiver pair and a quasi-cooperative transponder. It proposes to use run-length limited coding to mitigate the background self-interference and spread-Doppler clutter with only a small decrease in communication rate. The proposed method applies to both binary phase-shift keying (BPSK) and quadrature-amplitude modulation (QAM) scheme and provides an increase in rate by up to a factor of two compared with previous methods.

Additionally, this work analyzes the use of frequency modulation and bi-phase waveform coding for the transmitted (interrogating) waveform for high precision range estimation of the transponder location. Compared to previous methods, optimal lower range sidelobes are achieved. Moreover, since both the transmitted (interrogating) waveform coding and transponder communication coding result in instantaneous phase modulation of the signal, cross-interference between localization and communication tasks exists. Phase discriminating algorithm is proposed to make it possible to separate the waveform coding from the communication coding, upon reception, and achieve localization with increased signal energy by up to 3 dB compared with previous reported results.

The joint communication-localization framework also enables a low-complexity receiver design because the same radio is used both for localization and communication.

Simulations comparing the performance of different codes corroborate the theoretical results and offer possible trade-off between information rate and clutter mitigation as well as a trade-off between choice of waveform-channel coding pairs. Experimental results from a brass-board microwave system in an indoor environment are also presented and discussed.

Coding Strategies for X-ray Tomography

This work focuses on the construction and application of coded apertures to compressive X-ray tomography. Coded apertures can be made in a number of ways, each method having an impact on system background and signal contrast. Methods of constructing coded apertures for structuring X-ray illumination and scatter are compared and analyzed. Apertures can create structured X-ray bundles that investigate specific sets of object voxels. The tailored bundles of rays form a code (or pattern) and are later estimated through computational inversion. Structured illumination can be used to subsample object voxels and make inversion feasible for low dose computed tomography (CT) systems, or it can be used to reduce background in limited angle CT systems.

On the detection side, coded apertures modulate X-ray scatter signals to determine the position and radiance of scatter points. By forming object dependent projections in measurement space, coded apertures multiplex modulated scatter signals onto a detector. The multiplexed signals can be inverted with knowledge of the code pattern and system geometry. This work shows two systems capable of determining object position and type in a 2D plane, by illuminating objects with an X-ray `fan beam,' using coded apertures and compressive measurements. Scatter tomography can help identify materials in security and medicine that may be ambiguous with transmission tomography alone.

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Coding Manuals

The VRAG-R is designed to assess the likelihood of violent or sexual reoffending among male offenders. The data set comprises demographic, criminal history, psychological assessment, and psychiatric information about the offenders gathered from institutional files together with post-release recidivism information. The VRAG-R is a twelve-item actuarial instrument and the scores on these items form part of the data set. Because one of the goals of the VRAG-R development project was to compare the VRAG-R to the VRAG, subjects' VRAG scores are included in this data set. Access to the VRAG-R dataset is restricted. Contact Data Services, Queen's University Library (academic.services@queensu.ca) for access.

City dweller aspirations for cities of the future: How do environmental and personal wellbeing feature?

This paper explores city dweller aspirations for cities of the future in the context of global commitments to radically reduce carbon emissions by 2050; cities contribute the vast majority of these emissions and a growing bulk of theworld's population lives in cities. The particular challenge of creating a carbon reduced future in democratic countries is that the measures proposed must be acceptable to the electorate. Such acceptability is fostered if carbon reduced ways of living are also felt to bewellbeing maximising. Thus the objective of the paper is to explore what kinds of cities people aspire to live in, to ascertain whether these aspirations align with or undermine carbon reduced ways of living, as well as personal wellbeing. Using a novel free associative technique, city aspirations are found to cluster around seven themes, encompassing physical and social aspects. Physically, people aspire to a city with a range of services and facilities, green and blue spaces, efficient transport, beauty and good design. Socially, people aspire to a sense of community and a safe environment. An exploration of these themes reveals that only a minority of the participants' aspirations for cities relate to lowering carbon or environmental wellbeing. Far more consensual is emphasis on, and a particular vision of, aspirations that will bring personal wellbeing. Furthermore, city dweller aspirations align with evidence concerning factors that maximise personal wellbeing but, far less, with those that produce lowcarbonways of living. In order to shape a lower carbon future that city dwellers accept the potential convergence between environmental and personal wellbeing will need to be capitalised on: primarily aversion to pollution and enjoyment of communal green space.

La lengua como canon y como objeto de crítica en la gramática normativa

La selección de las muestras de ejemplos que se emplean en la codificación normativa del español está relacionada con las concepciones teóricas que en cada época histórica sirven de base para acometer la reflexión gramatical. La autoridad sobre el uso ha correspondido tradicionalmente en la preceptiva académica a las fuentes literarias, que se han empleado fundamentalmente para ilustrar la pauta normativa tanto en la labor lexicográfica como en la gramatical. La incorporación de nuevas tipologías textuales en la producción académica está vinculada a un cambio en la concepción teórica en la que una lengua ya no es concebida como un bloque monolítico y homogéneo, sino donde la variación lingüística se constituye en rasgo inherente a su misma condición histórica. De ahí que no resulte extraño que en la nómina de textos sea cada vez más frecuente encontrar un amplio corpus conformado por publicaciones periódicas. Esta incorporación de muestras periodísticas en la reciente producción académica, materializada en el Diccionario panhispánico de dudas (2005) y en la Nueva gramática de la lengua española (2009), viene a suplir en cierta medida también el silencio normativo académico ante las dudas y vacilaciones lingüísticas planteadas por los profesionales de los medios de comunicación. Tras el rastreo histórico de la aparición de muestras periodísticas en la ejemplificación normativa académica, se tratará de establecer si se ha producido un cambio en la funcionalidad de estas citas de manera que no sean ya empleadas exclusivamente con la valoración de ejemplaridad idiomática, tal y como se utilizaban fundamentalmente las muestras extraídas de los textos literarios en la labor de codificación tradicional de la Academia, sino también como variantes incorrectas objeto de una crítica más o menos velada hacia determinados usos circunscritos mayoritariamente al discurso periodístico actual.

Feature recognition & tool path generation for 5 axis step-nc machining of free form / irregular contoured surfaces

This research paper presents a five step algorithm to generate tool paths for machining Free form / Irregular Contoured Surface(s) (FICS) by adopting STEP-NC (AP-238) format. In the first step, a parametrized CAD model with FICS is created or imported in UG-NX6.0 CAD package. The second step recognizes the features and calculates a Closeness Index (CI) by comparing them with the B-Splines / Bezier surfaces. The third step utilizes the CI and extracts the necessary data to formulate the blending functions for identified features. In the fourth step Z-level 5 axis tool paths are generated by adopting flat and ball end mill cutters. Finally, in the fifth step, tool paths are integrated with STEP-NC format and validated. All these steps are discussed and explained through a validated industrial component.