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Meta-analysis on central line–associated bloodstream infections associated with a needleless intravenous connector with a new engineering design
Intravenous needleless connectors (NCs) with a desired patient safety design may facilitate effective intravenous line care and reduce the risk for central line–associated bloodstream infection (CLA-BSI). We conducted a meta-analysis to determine the risk for CLA-BSI associated with the use of a new NC with an improved engineering design. We reviewed MEDLINE, Cochrane Database of Systematic R...


Sort-mid tasks scheduling algorithm in grid computing
Scheduling tasks on heterogeneous resources distributed over a grid computing system is an NP-complete problem. The main aim for several researchers is to develop variant scheduling algorithms for achieving optimality, they have shown a good performance for tasks scheduling regarding resources selection. However, using of the full power of resources is still a challenge. In this paper, a new he...
Accuracy bounds of non-Gaussian Bayesian tracking in a NLOS environment
With a growth of the popularity of wireless sensor networks it has became obvious that Bayesian filter is most commonly used method for the sensor localization. The multiple sensors in one device allow to build different variations of the filter through the definition of the components of Bayesian rule. This paper presents a localization algorithm that is based on Bayesian filter and an attempt...


Zero-forcing DPC beamforming design for multiuser MIMO broadcast channels
The sum rate maximization in multiuser MIMO broadcast channels is investigated in this paper. We first propose an approach under a total power constraint. Compared with the most related methods in the literature, the proposed method can be easily adapted to a more realistic per-antenna power constraint. Since the power of each antenna is limited individually by the linearity of its power amplif...
Two-level ℓ1 minimization for compressed sensing
Compressed sensing using ℓ1 minimization has been widely and successfully applied. To further enhance the sparsity, a non-convex and piecewise linear penalty is proposed. This penalty gives two different weights according to the order of the absolute value and hence is called the two-level ℓ1-norm. The two-level ℓ1-norm can be minimized by an iteratively reweighted ℓ1 method. Compared w...


Adaptive detection and estimation for an unknown occurring interval signal in correlated Gaussian noise
This paper considers the problem of detecting and estimating an unknown occurring interval signal in correlated Gaussian noise, which is often arisen in signal processing society, e.g., identifying the onset times of a seismic wave and detecting a distributed target in unknown occurring range cells. We propose the novel Generalized Likelihood Ratio Test (GLRT) algorithm, where the Maximum Likel...
Drift removal by means of alternating least squares with application to Herschel data
We consider the problem of reconstructing an image observed with a linear, noisy instrument, the output of which is affected by a drift too, causing a slowly varying deviation of the readouts from the baseline level. Since the joint estimation of the image and the drift, which is the optimal approach, is demanding for large data, we consider an alternative approach, where we remove the drift an...

Do chaos-based communication systems really transmit chaotic signals?
Many communication systems based on the synchronism of chaotic systems have been proposed as an alternative spread spectrum modulation that improves the level of privacy in data transmission. However, depending on the map and on the encoding function, the transmitted signal may cease to be chaotic. Therefore, the sensitive dependence on initial conditions, which is one of the most interesting p...
Parametric Rao test for multichannel adaptive detection of range-spread target in partially homogeneous environments
In this paper we deal with the problem of detecting a multi-channel signal of range-spread target in the presence of Gaussian disturbance with an unknown covariance matrix. In particular, we consider the so-called partially homogeneous environment, where the disturbances in both the cells under test (primary data) and the training samples (secondary data) share the same covariance matrix up to ...

Constant turn model for statically fused converted measurement Kalman filters
In this paper, the discrete temporal evolution equation of pseudo-states is derived for the constant turn (CT) motion with known turn rate. The pseudo-state vector consists of the converted Doppler (the product of target true range and range rate) and its first derivative. Based on the resulting linear state equation, the converted Doppler measurement Kalman filter (CDMKF) is formulated to extr...
EMD interval thresholding denoising based on similarity measure to select relevant modes
This paper introduces a novel EMD interval thresholding (EMD-IT) denoising, where relevant modes are selected using a l 2-norm measure between the probability density function (pdf) of the input and that of each mode, thresholds are estimated by the characteristics of fractional Gaussian noise (fGn) through EMD. To solve the problem of more relevant modes included when the signal is corrupted b...

Legendre nonlinear filters
The paper discusses a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. The novel sub-class combines the best characteristics of truncated Volterra filters and of the recently introduced even mirror Fourier nonlinear filters, in particular: (i) Legendre nonlinear filters can arbitrarily well approximate any causal, time-invariant, finite-memory, cont...
Scrambling–embedding for JPEG compressed image
This paper proposes a novel reversible unified information hiding method for the JPEG compressed image, aiming to achieve scrambling and external data insertion simultaneously. The properties of DC coefficients, energy of AC coefficient block, and run of zero AC coefficients are exploited. Two techniques are proposed to degrade the perceptual quality while manipulating the DCT coefficients for ...
Robust Huber similarity measure for image registration in the presence of spatially-varying intensity distortion
Similarity measure is an important part of image registration. The main challenge of similarity measure is lack of robustness to different distortions. A well-known distortion is spatially-varying intensity distortion. Its main characteristic is correlation among pixels. Most traditional intensity based similarity measures (e.g., SSD, MI) assume stationary image and pixel to pixel independence....
Image denoising via bivariate shrinkage function based on a new structure of dual contourlet transform
Image denoising is a basic procedure of image processing, and the purpose of image denoising is to remove noises entirely and well preserve image boundaries and texture information simultaneously. However, conventional filtering methods easily lead to the loss of texture and details information. This paper proposes a new image denoising method to improve this problem, first proposing a new stru...