2,372 research outputs found
Astrophysical Fluid Dynamics via Direct Statistical Simulation
In this paper we introduce the concept of Direct Statistical Simulation (DSS)
for astrophysical flows. This technique may be appropriate for problems in
astrophysical fluids where the instantaneous dynamics of the flows are of
secondary importance to their statistical properties. We give examples of such
problems including mixing and transport in planets, stars and disks. The method
is described for a general set of evolution equations, before we consider the
specific case of a spectral method optimised for problems on a spherical
surface. The method is illustrated for the simplest non-trivial example of
hydrodynamics and MHD on a rotating spherical surface. We then discuss possible
extensions of the method both in terms of computational methods and the range
of astrophysical problems that are of interest.Comment: 26 pages, 11 figures, added clarifying remarks and references, and
corrected typos. This version is accepted for publication in The
Astrophysical Journa
Health promotion, disease prevention and periodic health checks: perceptions and practice among family physicians in eastern Mediterranean region
Introduction: The aim of this study was to identify the current practices and perceptions of family physicians regarding health promotion, disease prevention including periodic screening and health checks in Eastern Mediterranean Region. Methods: A multi-country cross-sectional study was conducted in six countries of EMR, from September 2014 to March 2015. Family Physicians who were currently practicing in different countries of EMR were invited to participate in the study through email. A pre-tested structured questionnaire was used for data collection. Data was entered and analyzed on SPSS 19 and logistic regression analysis was performed. Results: A total of 100 physicians data was included in the final analysis. The majority were female physicians (76%): 63% were 25 to 35 years of age. Approximately 53% of Family physicians always recommend periodic screening and health checks to their patients. The common screening question asked to patients in medical history was related to their blood pressure (86%). Almost all (99%) of the Family physicians believe they should conduct periodic health checks. Those who had postgraduate training in Family Medicine (OR: 0.5; 95% CI: 0.39-1.67) and attended CME sessions regularly (OR: 0.11; 95% CI: 0.01-0.93), are more likely to recommend periodic screening and health checks to their patients. Conclusion: Periodic screening and health check is an important strategy to prevent disease and maintain health. It is an underutilized practice and a great need exists for its implementation in family practice
Simulation of the fatigue behaviour of a power plant steel with a damage variable
The fatigue behaviour of a 9Cr power plant steel at a temperature of 600 °C was studied by uniaxial fatigue tests and microstructural analysis using electron microscopy. A continuum damage mechanics apporach was coupled to the constitutive equations of the Chaboche elasto-visco-plastic model to describe the fatigue behaviour of the 9Cr power plant steel at 600 °C. A stress partition method is introduced to understand the fatigue softening behaviour, and used to give an initial estimate of the material constants in the Chaboche model. Further optimisation procedures with plastic strain range dependency of the material constants were introduced in the optimisation procedure in order to accurately predict the material behaviour, especially after damage initiation. An ABAQUS UMAT subroutine was coded to allow the full life cyclic softening behaviour of a power plant component to be accurately predicted in a finite element calculation. The multiaxial capability of the coding is validated against notched bar test data
Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques.
State of charge (SOC) is a crucial index used in the assessment of electric vehicle (EV) battery storage systems. Thus, SOC estimation of lithium-ion batteries has been widely investigated because of their fast charging, long-life cycle, and high energy density characteristics. However, precise SOC assessment of lithium-ion batteries remains challenging because of their varying characteristics under different working environments. Machine learning techniques have been widely used to design an advanced SOC estimation method without the information of battery chemical reactions, battery models, internal properties, and additional filters. Here, the capacity of optimized machine learning techniques are presented toward enhanced SOC estimation in terms of learning capability, accuracy, generalization performance, and convergence speed. We validate the proposed method through lithium-ion battery experiments, EV drive cycles, temperature, noise, and aging effects. We show that the proposed method outperforms several state-of-the-art approaches in terms of accuracy, adaptability, and robustness under diverse operating conditions
Terahertz Security Image Quality Assessment by No-reference Model Observers
To provide the possibility of developing objective image quality assessment
(IQA) algorithms for THz security images, we constructed the THz security image
database (THSID) including a total of 181 THz security images with the
resolution of 127*380. The main distortion types in THz security images were
first analyzed for the design of subjective evaluation criteria to acquire the
mean opinion scores. Subsequently, the existing no-reference IQA algorithms,
which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and
BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM,
CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security
image quality. The statistical results demonstrated the superiority of Fish_bb
over the other testing IQA approaches for assessing the THz image quality with
PLCC (SROCC) values of 0.8925 (-0.8706), and with RMSE value of 0.3993. The
linear regression analysis and Bland-Altman plot further verified that the
Fish__bb could substitute for the subjective IQA. Nonetheless, for the
classification of THz security images, we tended to use S3 as a criterion for
ranking THz security image grades because of the relatively low false positive
rate in classifying bad THz image quality into acceptable category (24.69%).
Interestingly, due to the specific property of THz image, the average pixel
intensity gave the best performance than the above complicated IQA algorithms,
with the PLCC, SROCC and RMSE of 0.9001, -0.8800 and 0.3857, respectively. This
study will help the users such as researchers or security staffs to obtain the
THz security images of good quality. Currently, our research group is
attempting to make this research more comprehensive.Comment: 13 pages, 8 figures, 4 table
Recommended from our members
Comparison of different iterative schemes for ISPH based on Rankine source solution
Smoothed Particle Hydrodynamics (SPH) method has a good adaptability for the simulation of free surface flow problems. There are two forms of SPH. One is weak compressible SPH and the other one is incompressible SPH (ISPH). Compared with the former one, ISPH method performs better in many cases. ISPH based on Rankine source solution can perform better than traditional ISPH, as it can use larger stepping length by avoiding the second order derivative in pressure Poisson equation. However, ISPH_R method needs to solve the sparse linear matrix for pressure Poisson equation, which is one of the most expensive parts during one time stepping calculation. Iterative methods are normally used for solving Poisson equation with large particle numbers. However, there are many iterative methods available and the question for using which one is still open. In this paper, three iterative methods, CGS, Bi-CGstab and GMRES are compared, which are suitable and typical for large unsymmetrical sparse matrix solutions. According to the numerical tests on different cases, still water test, dam breaking, violent tank sloshing, solitary wave slamming, the GMRES method is more efficient than CGS and Bi-CGstab for ISPH method
Alcohol-dysregulated microRNAs in hepatitis B virus-related hepatocellular carcinoma
published_or_final_versio
Provably secure and efficient audio compression based on compressive sensing
The advancement of systems with the capacity to compress audio signals and simultaneously secure is a highly attractive research subject. This is because of the need to enhance storage usage and speed up the transmission of data, as well as securing the transmission of sensitive signals over limited and insecure communication channels. Thus, many researchers have studied and produced different systems, either to compress or encrypt audio data using different algorithms and methods, all of which suffer from certain issues including high time consumption or complex calculations. This paper proposes a compressing sensing-based system that compresses audio signals and simultaneously provides an encryption system. The audio signal is segmented into small matrices of samples and then multiplied by a non-square sensing matrix generated by a Gaussian random generator. The reconstruction process is carried out by solving a linear system using the pseudoinverse of Moore-Penrose. The statistical analysis results obtaining from implementing different types and sizes of audio signals prove that the proposed system succeeds in compressing the audio signals with a ratio reaching 28% of real size and reconstructing the signal with a correlation metric between 0.98 and 0.99. It also scores very good results in the normalized mean square error (MSE), peak signal-to-noise ratio metrics (PSNR), and the structural similarity index (SSIM), as well as giving the signal a high level of security
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