Problem Of Compression Research Articles

Convective Rolls in a Compressible Fluid

Rayleigh-Bénard convection occurs between two horizontally infinite plates when the lower plate is heated with respect to the upper one. The temperature gradient between the two plates causes convective rolls to form as the warmer fluid below becomes more buoyant than the cooler fluid above it. The standard (classical) analysis uses the Boussinesq approximation, which neglects the variations of fluid density except in relation to buoyancy forces. This approximation is not accurate for some real-world applications. This project is inspired by the atmosphere, so we will consider the onset of convection in a vertically stratified layer of fluid which we model using the anelastic equations. The standard analysis is presented in many textbooks and is used as a comparison to the analysis for the compressible fluid presented here. Using linear stability analysis, we compute the critical temperature differences required to induce convection. It is not possible to find analytical solutions, and therefore, numerical methods implemented in Python using LAPACK subroutines are used. Results of the critical Rayleigh number at the half-height of the fluid for a range of plate separation distances are computed. For all the cases that are considered, the solution for the compressible problem follows the standard solution for plate separation distances smaller than some viscosity-dependent value that increases with the viscosity of the fluid. For larger d, it is observed that the stratification inhibits the onset of convection. Our solution is far more idealized than any actual convection happening in the atmosphere. However, it does demonstrate, in this context, the limits of the Boussinesq approximation.

Nonstationary Double-Deck Structure of Boundary Layers in Compressible Flow Problem Inside a Channel with Small Irregularities on the Walls

Nonstationary Double-Deck Structure of Boundary Layers in Compressible Flow Problem Inside a Channel with Small Irregularities on the Walls

Multidimensional spatial transformation of streaming video in satellite communication channels

The problem of compression of high-resolution streaming video for transmission over low-speed satellite communication channels of small spacecraft is considered. It has been determined that the specificity of using small spacecraft in low orbits, on the one hand, imposes a number of restrictions on weight and size characteristics and energy consumption, on the other hand, it opens up new opportunities for obtaining high-resolution visual information. Approaches to real-time video data compression are considered, which make it possible to implement a subminiature encoder in the “system-onchip” basis. A coding method based on the complex principles of AV1 coding and multidimensional spatial transformation is proposed. The practical attainability of the developed method and algorithms is shown. The ways of developing the method and creating a video data compression system are proposed.

Online MECG Compression Based on Incremental Tensor Decomposition for Wearable Devices.

Lightweight and real-time multi-lead electrocardiogram (MECG) compression on wearable devices is important and challenging for long-term health monitoring. To utilize all three kinds of correlations of MECG data simultaneously, we construct 3-order incremental tensor and formulate data compression problem as tensor decomposition. However, the conventional tensor decomposition algorithms for large-scale tensor are usually too computationally expensive to apply to wearable devices. To reduce the computation complexity, we develop online compression approach by incremental tracking the CANDECOMP/PARAFAC (CP) decomposition of dynamic incremental tensors, which can efficiently utilize the tensor compression result based on the previous MECG data to derive the tensor compression upon arriving of new data. We evaluate the performance of our method with the Physikalisch-Technische Bundesanstalt MECG diagnostic dataset. Our method can achieve the averaged percentage root-mean-square difference (PRD) of 8.35% ±2.28% and the compression ratio (CR) of 43.05 ±2.01, which is better than five state-of-the-art of methods. Additionally, it can also well preserve the information of R-peak. Our method is suitable for near real-time MECG compression on wearable devices.

State-Temporal Compression in Reinforcement Learning With the Reward-Restricted Geodesic Metric.

It is difficult to solve complex tasks that involve large state spaces and long-term decision processes by reinforcement learning (RL) algorithms. A common and promising method to address this challenge is to compress a large RL problem into a small one. Towards this goal, the compression should be state-temporal and optimality-preserving (i.e., the optimal policy of the compressed problem should correspond to that of the uncompressed problem). In this paper, we propose a reward-restricted geodesic (RRG) metric, which can be learned by a neural network, to perform state-temporal compression in RL. We prove that compression based on the RRG metric is approximately optimality-preserving for the raw RL problem endowed with temporally abstract actions. With this compression, we design an RRG metric-based reinforcement learning (RRG-RL) algorithm to solve complex tasks. Experiments in both discrete (2D Minecraft) and continuous (Doom) environments demonstrated the superiority of our method over existing RL approaches.

Ultra-High-Resolution IonStar Strategy Enhancing Accuracy and Precision of MS1-Based Proteomics and an Extensive Comparison with State-of-the-Art SWATH-MS in Large-Cohort Quantification.

Quantitative proteomics in large cohorts is highly valuable for clinical/pharmaceutical investigations but often suffers from severely compromised reliability, accuracy, and reproducibility. Here, we describe an ultra-high-resolution IonStar method achieving reproducible protein measurement in large cohorts while minimizing the ratio compression problem, by taking advantage of the exceptional selectivity of ultra-high-resolution (UHR)-MS1 detection (240k_FWHM@m/z = 200). Using mixed-proteome benchmark sets reflecting large-cohort analysis with technical or biological replicates (N = 56), we comprehensively compared the quantitative performances of UHR-IonStar vs a state-of-the-art SWATH-MS method, each with their own optimal analytical platforms. We confirmed a cutting-edge micro-liquid chromatography (LC)/Triple-TOF with Spectronaut outperforms nano-LC/Orbitrap for SWATH-MS, which was then meticulously developed/optimized to maximize sensitivity, reproducibility, and proteome coverage. While the two methods with distinct principles (i.e., MS1- vs MS2-based) showed similar depth-of-analysis (∼6700-7000 missing-data-free proteins quantified, 1% protein-false discovery rate (FDR) for entire set, 2 unique peptides/protein) and good accuracy/precision in quantifying high-abundance proteins, UHR-IonStar achieved substantially superior quantitative accuracy, precision, and reproducibility for lower-abundance proteins (a category that includes most regulatory proteins), as well as much-improved sensitivity/selectivity for discovering significantly altered proteins. Furthermore, compared to SWATH-MS, UHR-IonStar showed markedly higher accuracy for a single analysis of each sample across a large set, which is an inadequately investigated albeit critical parameter for large-cohort analysis. Finally, we compared UHR-IonStar vs SWATH-MS in measuring the time courses of altered proteins in paclitaxel-treated cells (N = 36), where dysregulated biological pathways have been very well established. UHR-IonStar discovered substantially more well-recognized biological processes/pathways induced by paclitaxel. Additionally, UHR-IonStar showed markedly superior ability than SWATH-MS in accurately depicting the time courses of well known to be paclitaxel-induced biomarkers. In summary, UHR-IonStar represents a reliable, robust, and cost-effective solution for large-cohort proteomic quantification with excellent accuracy and precision.

Fundamental Limits of Lossless Data Compression With Side Information

The problem of lossless data compression with side information available to both the encoder and the decoder is considered. The finite-blocklength fundamental limits of the best achievable performance are defined, in two different versions of the problem: Reference-based compression, when a single side information string is used repeatedly in compressing different source messages, and pair-based compression, where a different side information string is used for each source message. General achievability and converse theorems are established for arbitrary source-side information pairs. Nonasymptotic normal approximation expansions are proved for the optimal rate in both the reference-based and pair-based settings, for memoryless sources. These are stated in terms of explicit, finite-blocklength bounds, that are tight up to third-order terms. Extensions that go significantly beyond the class of memoryless sources are obtained. The relevant source dispersion is identified and its relationship with the conditional varentropy rate is established. Interestingly, the dispersion is different in reference-based and pair-based compression, and it is proved that the reference-based dispersion is in general smaller.

Compressive Sensing: Methods, Techniques, and Applications

According to the latest research, it is very much clear that in future we require a huge amount of data as modern advancement in communication and signal processing generates a large number of bytes some examples are 5G peak data rate about 300 Mb/sec, an image of black hole required several petabytes to store & in medical signal processing huge amount of data required. So, by these examples, we can easily understand the scarcity of storage in near future. To overcome this problem of data scarcity such type of data compression is required in which the information of the signal will not be degraded. A well-known method is Compressive Sensing which can easily tackle this problem of data compression.

Leibenzon-Ishlinsky Criterion for the Axisymmetric Problem of Compression of the Pillar

In the framework of the Leibenzon-Ishlinsky approach, the problem of the loss of stability of a pillar of a cylindrical mine working is solved. The pillar material was assumed with an initial anisotropy corresponding to the layered structure. A criterion for loss of stability is being constructed, a solution to the system of differential equations of the problem in the form of combinations of cylindrical and trigonometric functions is determined. From the fact that the determinant of a system of homogeneous algebraic equations is equal to zero, the critical load value is found at which, along with the main continuation of the deformation of the pillar, something else is possible with a changed surface geometry. The influence of the initial anisotropy, the parameters of the pillar (height, radius) on the values of the ultimate load is investigated.

Three new lengths for cyclic Legendre pairs

Introduction: It is conjectured that the cyclic Legendre pairs of odd lengths >1 always exist. Such a pair consists of two functions a, b: G→Z, whose values are +1 or −1, and whose periodic autocorrelation function adds up to the constant value −2 (except at the origin). Here G is a finite cyclic group and Z is the ring of integers. These conditions are fundamental and the closely related structure of Hadamard matrices having a two circulant core and double border is incompletely described in literature, which makes its study especially relevant. Purpose: To describe the two-border two-circulant-core construction for Legendre pairs having three new lengths. Results: To construct new Legendre pairs we use the subsets X={x∈G: a(x)=–1} and Y={x∈G: b(x)=–1} of G. There are 20 odd integers v less than 200 for which the existence of Legendre pairs of length v is undecided. The smallest among them is v=77. We have constructed Legendre pairs of lengths 91, 93 and 123 reducing thereby the number of undecided cases to 17. In the last section of the paper we list some new examples of cyclic Legendre pairs for lengths v≤123. Practical relevance: Hadamard matrices are used extensively in the problems of error-free coding, and compression and masking of video information. Programs for search of Hadamard matrices and a library of constructed matrices are used in the mathematical network “mathscinet.ru” together with executable on-line algorithms

Top van de ijsberg: indrukwekkende intrathoracale goiter

Tip of the iceberg: massive intrathoracic goiter In this article a case of an 80 year-old man with an impressive intrathoracic goiter is described. Thorough evaluation of the structural and functional impact and the risk of malignancy is needed. Theoretically, the management can consist of surgical resection, radioactive iodine, anti-thyroid drugs (in case of hyperthyroidism), or active surveillance. Multidisciplinary consultation is essential in cases of goiter with an important intrathoracic component. Based on the absence of compressive problems, the mild hyperthyroidism, the low risk of thyroid cancer and the anticipated slow growth, an active surveillance strategy was chosen.

Compression-Based Methods of Time Series Forecasting

Time series forecasting is an important research topic with many practical applications. As shown earlier, the problems of lossless data compression and prediction are very similar mathematically. In this article, we propose several forecasting methods based on real-world data compressors. We consider predicting univariate and multivariate data, describe how multiple data compressors can be combined into one forecasting method with automatic selection of the best algorithm for the input data. The developed forecasting techniques are not inferior to the known ones. We also propose a way to reduce the computation time of the combined method by using the so-called time-universal codes. To test the proposed techniques, we make predictions for real-world data such as sunspot numbers and some social indicators of Novosibirsk region, Russia. The results of our computations show that the described methods find non-trivial regularities in data, and time universal codes can reduce the computation time without losing accuracy.

Investigation of the Fracture of a Semibounded Body Compressed Along a Near-Surface Interface Crack

We consider the problem of compression of a piecewise homogeneous half plane by forces directed along a near-surface crack located on the interface of two materials. This problem belongs to the class of nonclassical problems of fracture mechanics because, for the analyzed loading scheme, the stressstrain state realized in the body is homogeneous and the corresponding expressions for stresses and displacements in the vicinity of the crack do not contain singular components. Due to the fact that the stress intensity factors are equal to zero, for the analyzed problem, the classical Griffith–Irwin fracture criteria are inapplicable. In the indicated situation, the onset of crack propagation is associated with the local loss of stability of the equilibrium state of a part of the material located in the region adjacent to the crack. By using the approaches of the three-dimensional linearized theory of stability of deformable bodies, we propose a mathematical statement of the problem and an approach to its investigation. By using the representations of stresses and displacements in terms of complex potentials, we analyze the case where the roots of the corresponding characteristic equation are identical for each material.

Compressive response of self-healing polymer foams containing bilayered capsules: Coupled healing agents diffusion and stress simulations

Numerical modelling on the compressive response of self-healing polymer foams embedded with novel, bilayered alginate capsules was developed based on the coupled pore fluid diffusion and stress simulations. Micromechanical models were developed to link the damage variable to permeability as well as the saturation to the capillary pressure within damaged polymer foams. These micromechanical models were calibrated against experimental measurements and were implemented into the coupled simulations. To give physical insight into how the damage evolution coupled with the mass conservation, an illustrative example was presented for one-dimensional (1D) compression problem. Two-dimensional (2D) detailed finite element simulations were conducted to interpret the experimental findings. It was demonstrated that the numerical study could capture the main features of the self-healing process. The predicted healing efficiency has good agreement with that measured by the experiments. Based on the numerical models, parameter study was conducted to understand the effects of the key design parameters of the healing system.

Particle regeneration technique for Smoothed Particle Hydrodynamics in simulation of compressible multiphase flows

In this work, a particle regeneration technique is developed for Smoothed Particle Hydrodynamics (SPH). In traditional SPH, the particle disorder phenomenon will occur when dealing with the strongly compressible flow problem. To solve this, in the present work, uniformly distributed background particles filled in the computational domain are adopted. The particle regeneration technique is that the fluid particles replaced by the background particles when the fluid density changes to a specific limitation. The fluid variables of the background particles are approximated by the fluid variables of the initial particles in their support domain. For the multiphase flow, the multiphase interface is calculated by an interface reproducing algorithm, in which, we defined an indicator variable, and set the indicator value discontinuity between different materials. By setting the threshold value, the multiphase interface is reconstructed. Meanwhile, the momentum equation for the Riemann SPH is modified to eliminate the instability in the light phase. Several numerical examples are studied to verify the present algorithm.

An Asynchronous Incomplete Block LU Preconditioner for Computational Fluid Dynamics on Unstructured Grids

We present a study of the effectiveness of asynchronous incomplete LU factorization preconditioners for the time-implicit solution of compressible flow problems while exploiting thread-parallelism within a compute node. A block variant of the asynchronous fine-grained parallel preconditioner adapted to a finite volume discretization of the compressible Navier--Stokes equations on unstructured grids is presented, and convergence theory is extended to the new variant. Experimental (numerical) results on the performance of these preconditioners on inviscid and viscous laminar two-dimensional steady-state test cases are reported. It is found, for these compressible flow problems, that the block variant performs much better in terms of convergence, parallel scalability, and reliability than the original scalar asynchronous ILU preconditioner. For viscous flow, it is found that the ordering of unknowns may determine the success or failure of asynchronous block-ILU preconditioning, and an ordering of grid cells suitable for solving viscous problems is presented.

Meshfree method based on discrete gas-kinetic scheme to simulate incompressible/compressible flows

A meshfree method based on the discrete gas-kinetic scheme (DGKS) (called the meshfree-DGKS) for simulation of incompressible/compressible flows is proposed in this work. In this approach, the governing equations are discretized using the meshfree method based on the least squares-based finite difference approach. To simulate compressible problems with discontinuities, the virtual mid-points between adjacent nodes, which are regarded as Riemann discontinuities, are established. Then, the concept of numerical flux is introduced, which enables computing both compressible and incompressible problems. The fluxes at the mid-points are calculated using the DGKS based on the discrete particle velocity model. The corresponding particle velocity components and distribution functions are integrated based on moment relations to obtain the flux. The meshfree-DGKS maintains the advantages of the meshless method as it is implemented at arbitrarily distributed nodes. This breaks through the limitations of the grid topology and is suitable to handle complex geometries. More importantly, the fluxes at the mid-point are reconstructed with the DGKS using the local solution of the Boltzmann equation, which can describe its physical properties well, thus easily and stably capturing the shock wave. In addition, the DGKS can simultaneously calculate inviscid and viscous fluxes when simulating viscous flow problems, which gives an improved algorithm consistency. Several representative examples, such as shock tube problems, implosion problem, couette flow, lid-driven cavity flow, flow in a channel with a backward-facing step, supersonic flow around a ramp segment, and flow around staggered NACA0012 biplane configuration, are simulated to validate the proposed meshfree-DGKS.

Dynamic and static response of a slightly compressible hyperelastic solid

The paper presents dynamic and static response of a slightly compressible hyperelastic solid. Material models under consideration are obtained by extending incompressible material models which are consistent second and third order approximation of existing stored energy function in terms of a deformation measure, namely MCMV and MCIZ. The problems of a uniaxial compression of a rod and a twisting column are solved using ABAQUS which is a powerful finite element program designed for general use in nonlinear problems. The models are defined with a help of user subroutine UHYPER. In the case of including dynamic effects, an implicit integration scheme available in the software is used. For the twisting column problem, results are compared against available in the ABAQUS library polynomial model where the volumetric stored energy function does not meet basic growth conditions. Experimental data on synthetic rubber neoprene published in the literature is utilized.

Denoising-Based Turbo Message Passing for Compressed Video Background Subtraction.

In this paper, we consider the compressed video background subtraction problem that separates the background and foreground of a video from its compressed measurements. The background of a video usually lies in a low dimensional space and the foreground is usually sparse. More importantly, each video frame is a natural image that has textural patterns. By exploiting these properties, we develop a message passing algorithm termed offline denoising-based turbo message passing (DTMP). We show that these structural properties can be efficiently handled by the existing denoising techniques under the turbo message passing framework. We further extend the DTMP algorithm to the online scenario where the video data is collected in an online manner. The extension is based on the similarity/continuity between adjacent video frames. We adopt the optical flow method to refine the estimation of the foreground. We also adopt the sliding window based background estimation to reduce complexity. By exploiting the Gaussianity of messages, we develop the state evolution to characterize the per-iteration performance of offline and online DTMP. Comparing to the existing algorithms, DTMP can work at much lower compression rates, and can subtract the background successfully with a lower mean squared error and better visual quality for both offline and online compressed video background subtraction.

Robust Linear Domain Decomposition Schemes for Reduced Nonlinear Fracture Flow Models

In this work, we consider compressible single-phase flow problems in a porous medium containing a fracture. In the fracture, a nonlinear pressure-velocity relation is prescribed. Using a non-overla...