6,319 research outputs found

    Image compression based on 2D Discrete Fourier Transform and matrix minimization algorithm

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    In the present era of the internet and multimedia, image compression techniques are essential to improve image and video performance in terms of storage space, network bandwidth usage, and secure transmission. A number of image compression methods are available with largely differing compression ratios and coding complexity. In this paper we propose a new method for compressing high-resolution images based on the Discrete Fourier Transform (DFT) and Matrix Minimization (MM) algorithm. The method consists of transforming an image by DFT yielding the real and imaginary components. A quantization process is applied to both components independently aiming at increasing the number of high frequency coefficients. The real component matrix is separated into Low Frequency Coefficients (LFC) and High Frequency Coefficients (HFC). Finally, the MM algorithm followed by arithmetic coding is applied to the LFC and HFC matrices. The decompression algorithm decodes the data in reverse order. A sequential search algorithm is used to decode the data from the MM matrix. Thereafter, all decoded LFC and HFC values are combined into one matrix followed by the inverse DFT. Results demonstrate that the proposed method yields high compression ratios over 98% for structured light images with good image reconstruction. Moreover, it is shown that the proposed method compares favorably with the JPEG technique based on compression ratios and image quality

    A posteriori error control for discontinuous Galerkin methods for parabolic problems

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    We derive energy-norm a posteriori error bounds for an Euler time-stepping method combined with various spatial discontinuous Galerkin schemes for linear parabolic problems. For accessibility, we address first the spatially semidiscrete case, and then move to the fully discrete scheme by introducing the implicit Euler time-stepping. All results are presented in an abstract setting and then illustrated with particular applications. This enables the error bounds to hold for a variety of discontinuous Galerkin methods, provided that energy-norm a posteriori error bounds for the corresponding elliptic problem are available. To illustrate the method, we apply it to the interior penalty discontinuous Galerkin method, which requires the derivation of novel a posteriori error bounds. For the analysis of the time-dependent problems we use the elliptic reconstruction technique and we deal with the nonconforming part of the error by deriving appropriate computable a posteriori bounds for it.Comment: 6 figure

    Entropy, fidelity, and double orthogonality for resonance states in two-electron quantum dots

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    Resonance states of a two-electron quantum dot are studied using a variational expansion with both real basis-set functions and complex scaling methods. The two-electron entanglement (linear entropy) is calculated as a function of the electron repulsion at both sides of the critical value, where the ground (bound) state becomes a resonance (unbound) state. The linear entropy and fidelity and double orthogonality functions are compared as methods for the determination of the real part of the energy of a resonance. The complex linear entropy of a resonance state is introduced using complex scaling formalism

    Geometrical effects on energy transfer in disordered open quantum systems

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    We explore various design principles for efficient excitation energy transport in complex quantum systems. We investigate energy transfer efficiency in randomly disordered geometries consisting of up to 20 chromophores to explore spatial and spectral properties of small natural/artificial Light-Harvesting Complexes (LHC). We find significant statistical correlations among highly efficient random structures with respect to ground state properties, excitonic energy gaps, multichromophoric spatial connectivity, and path strengths. These correlations can even exist beyond the optimal regime of environment-assisted quantum transport. For random configurations embedded in spatial dimensions of 30 A and 50 A, we observe that the transport efficiency saturates to its maximum value if the systems contain 7 and 14 chromophores respectively. Remarkably, these optimum values coincide with the number of chlorophylls in (Fenna-Matthews-Olson) FMO protein complex and LHC II monomers, respectively, suggesting a potential natural optimization with respect to chromophoric density.Comment: 11 pages, 10 figures. Expanded from the former appendix to arXiv:1104.481

    Bootstrap for Critical Branching Process with Non-Stationary Immigration

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    2000 Mathematics Subject Classification: Primary 60J80, Secondary 62F12, 60G99.In the critical branching process with a stationary immigration the standard parametric bootstrap for an estimator of the offspring mean is invalid. We consider the process with non-stationary immigration, whose mean and variance α(n) and β(n) are finite for each n ≥ 1 and are regularly varying sequences with nonnegative exponents α and β, respectively. It turns out that if α(n) → ∞ and β(n) = o(nα2(n)) as n → ∞, then the standard parametric bootstrap procedure leads to a valid approximation for the distribution of the conditional least squares estimator. We state a theorem which justifies the validity of the bootstrap. By Monte-Carlo and bootstrap simulations for the process we confirm the theoretical findings. The simulation study highlights the validity and utility of the bootstrap in this model as it mimics the Monte-Carlo pivots even when generation size is small

    Smart cards and the fingerprint: a framework for user identification and authentication

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    Access control has been a great concern in this Information and Communication Technology (ICT) era. The need to control access to certain information and resources has been taken seriously by the ICT community. This research believes that no single security method, algorithm, key or procedure is entirely secure. Hence, a combination of multiple security components is mandatory to provide a high level of protection against fraud and other threats. This research combines two security components, which are the smart card and fingerprint recognition. It looks into the vulnerabilities of magnetic-stripe cards and Personal Identification Numbers (PIN) or passwords widely used in systems today. As a result, the research proposed a framework for user identification and authentication in automatic-teller-machine (ATM) systems using fingerprints and smart cards as opposed to the PIN and magnetic-stripe cards

    Effect of intravenous lidocaine infusion on sevoflurane requirements as monitored by bispectral index: A randomized double-blinded controlled study

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    AbstractIntroductionSystemic administration of lidocaine significantly decreased propofol requirements when compared to patients receiving placebo. Several studies conducted on animals have proved that systemic local anesthetics reduced minimum alveolar concentration (MAC) of inhalational anesthetics. The aim of this investigation is to study the effect of intravenous administration of lidocaine on the minimum alveolar concentration of sevoflurane required to keep BIS between 40 and 60 during maintenance of anesthesia in humans.MethodsTwenty-eight ASA I–II adults planned to undergo laparoscopic procedures expected to last <2h under general anesthesia were randomly assigned to 2 groups. After standardized induction of general anesthesia, patients were given IV lidocaine bolus (1.5mgkg−1) followed by 2mgkg−1h−1 infusion (group L, n=14) or equal volumes of saline (group C, n=14). Primary outcome of the study was end-tidal sevoflurane at bispectral index (BIS) values of 40–60. Secondary outcomes included doses of opioids, BIS values, and extubation time.ResultsThe median doses of intraoperative fentanyl (range) in group C were similar to group L (P=0.08). There were no significant differences between the 2 groups regarding BIS at any time point. End-tidal sevoflurane concentrations were significantly higher in group C than in group L at all intraoperative time points (P<0.05). Extubation time was longer in group L than in group C (P=0.04).ConclusionIn conclusion, intravenous lidocaine administration, during maintenance of general anesthesia, can decrease BIS-guided sevoflurane requirements

    Real time ear recognition using deep learning

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    Automatic identity recognition of ear images represents an active area of interest within the biometric community. The human ear is a perfect source of data for passive person identification. Ear images can be captured from a distance and in a covert manner; this makes ear recognition technology an attractive choice for security applications and surveillance in addition to related application domains. Differing from other biometric modalities, the human ear is neither affected by expressions like faces are nor do need closer touching like fingerprints do. In this paper, a deep learning object detector called faster region based convolutional neural networks (Faster R-CNN) is used for ear detection. A convolutional neural network (CNN) is used as feature extraction. principal component analysis (PCA) and genetic algorithm are used for feature reduction and selection respectively and a fully connected artificial neural network as a matcher. The testing proved the accuracy of 97.8% percentage of success with acceptable speed and it confirmed the accuracy and robustness of the proposed system
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