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Improving resolution of miniature spectrometers by exploiting sparse nature of signals.
Oliver, J,Lee, Woongbi,Park, Sangjun,Lee, Heung-No Optical Society of America 2012 Optics express Vol.20 No.3
<P>In this paper, we present a signal processing approach to improve the resolution of a spectrometer with a fixed number of low-cost, non-ideal filters. We aim to show that the resolution can be improved beyond the limit set by the number of filters by exploiting the sparse nature of a signal spectrum. We consider an underdetermined system of linear equations as a model for signal spectrum estimation. We design a non-negative L1 norm minimization algorithm for solving the system of equations. We demonstrate that the resolution can be improved multiple times by using the proposed algorithm.</P>
Oliver-Calixte, Nyoté,J.,Uba, Franklin I.,Battle, Katrina N.,Weerakoon-Ratnayake, Kumuditha M.,Soper, Steven A. American Chemical Society 2014 ANALYTICAL CHEMISTRY - Vol.86 No.9
<P>The process of immobilizing enzymes onto solid supports for bioreactions has some compelling advantages compared to their solution-based counterpart including the facile separation of enzyme from products, elimination of enzyme autodigestion, and increased enzyme stability and activity. We report the immobilization of λ-exonuclease onto poly(methylmethacrylate) (PMMA) micropillars populated within a microfluidic device for the on-chip digestion of double-stranded DNA. Enzyme immobilization was successfully accomplished using 3-(3-dimethylaminopropyl) carbodiimide/<I>N</I>-hydroxysuccinimide (EDC/NHS) coupling to carboxylic acid functionalized PMMA micropillars. Our results suggest that the efficiency for the catalysis of dsDNA digestion using λ-exonuclease, including its processivity and reaction rate, were higher when the enzyme was attached to a solid support compared to the free solution digestion. We obtained a clipping rate of 1.0 × 10<SUP>3</SUP> nucleotides s<SUP>–1</SUP> for the digestion of λ-DNA (48.5 kbp) by λ-exonuclease. The kinetic behavior of the solid-phase reactor could be described by a fractal Michaelis–Menten model with a catalytic efficiency nearly 17% better than the homogeneous solution-phase reaction. The results from this work will have important ramifications in new single-molecule DNA sequencing strategies that employ free mononucleotide identification.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancham/2014/ancham.2014.86.issue-9/ac5002965/production/images/medium/ac-2014-002965_0006.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/ac5002965'>ACS Electronic Supporting Info</A></P>
Oliver Eberhardt,Thomas Wallmersperger 국제구조공학회 2014 Smart Structures and Systems, An International Jou Vol.13 No.4
Carbon nanotubes are due to their outstanding mechanical properties destined for a wide range of possible applications. Since the knowledge of the material behavior is vital regarding the possible applications, experimental and theoretical studies have been conducted to investigate the properties of this promising material. The aim of the present research is the calculation of mechanical properties and of the mechanical behavior of single wall carbon nanotubes (SWCNTs). The numerical simulation was performed on basis of a molecular mechanics approach. Within this approach two different issues were taken into account: (i) the nanotube geometry and (ii) the modeling of the covalent bond. The nanotube geometry is captured by two different approaches, the roll-up and the exact polyhedral model. The covalent bond is modeled by a structural molecular mechanics approach according to Li and Chou. After a short introduction in the applied modeling techniques, the results for the Young\'s modulus for several SWCNTs are presented and are discussed extensively. The obtained numerical results are compared to results available in literature and show an excellent agreement. Furthermore, deviations in the geometry stemming from the different models are given and the resulting differences in the numerical findings are shown. Within the investigation of the deformation mechanisms occurring in SWCNTs, the basic contributions of each individual covalent bond are considered. The presented results of this decomposition provide a deeper understanding of the governing deformation mechanisms in SWCNTs.
Applications of Ward Network and GRNN for Corn Quality Classification
Oliver C. Agustin,Byung-Joo Oh 한국정보기술학회 2007 한국정보기술학회논문지 Vol.5 No.4
We present the methods of identifying the mold contents in corn kernel classification. We evaluated two neural networks architectures, namely, general regression neural network(GRNN) and Ward network which is a combination of many slabs with different activation functions. The extraction features used in this paper is entirely based on the internal features of the kernel, specifically the color features. Several techniques have been developed by researchers in which the choice of the appropriate method entirely depends on factors such as implementation, cost, nature of the problem and its scope. A prototype has been successfully implemented that utilizes the trained Ward network in visual basic 2005 as a proof of the method. The initial result in this work showed exceptional results in GRNN as corn quality classification.