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Wavelet shrinkage schemes are applied for reducing noise in synthetic and experimental ultrasonic A-scans, using the Discrete Wavelet Transform (DWT) and a cycle-spinning (CS) implementation of Undecimated Wavelet Transform (UWT). A new wavelet-based denoising procedure, which we call Random Partial Cycle Spinning (RPCS) is presented and its performance is compared with that of DWT and a CS implementation of UWT. Three well known threshold selection rules (Universal, Minimax and Sure), with decomposition level dependent threshold selection, are used in all cases. Denoising using the UWT has previously shown a robust and usually better performance than denoising using DWT but with a much higher computational cost. In this work, it is shown that the alternative procedure RPCS provides a good robust performance, close to CS performance, but with a much lower computational cost.

Wavelets are a powerful tool for signal and image denoising. Most of the denoising applications in different fields were based on the thresholding of the discrete wavelet transform (DWT) coefficients. Nevertheless, DWT transform is not a time or shift invariant transform and results depend on the selected shift. Improvements on the denoising performance can be obtained using the stationary wavelet transform (SWT) (also called shift-invariant or undecimated wavelet transform). Denoising using SWT has previously shown a robust and usually better performance than denoising using DWT but with a higher computational cost. In this paper, wavelet shrinkage schemes are applied for reducing noise in synthetic and experimental non-destructive evaluation (NDE) ultrasonic A-scans, using DWT and a cycle-spinning implementation of SWT.A new denoising procedure, which we call Random Partial Cycle Spinning (RPCS), is presented. It is based on a cycle-spinning over a limited number of shifts that are selected in a random way. Wavelet denoising based on DWT, SWT and RPCS have been applied to the same sets of ultrasonic A-scans and their performances in terms of SNR are compared. In all cases three well known threshold selection rules (Universal, Minimax and Sure), with decomposition level dependent selection, have been used. It is shown that the new procedure provides a good robust denoising performance, without the DWT fluctuating performance, and close to SWT but with a much lower computational cost.

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The concept of Smart-Hospital is generally associated with a comprehensive care model capable of responding to the needs of health institutions, companies and patients in an optimum way in terms of economic, operative and environmental aspects aiming the improvement of care quality and sustainable use of resources. In this context, a Smart-Hospital is a technological and hyper-connected hospital in terms of telecommunications. A huge range of systems and devices generate information of a heterogeneous nature. In many cases, for reasons of efficiency and availability, this information is stored and processed in architectures external to the hospital itself. Centralized services housed in Cloud architectures or telemedicine / tele-assistance services are proof of this. Guaranteeing an adequate level of quality of service is a complex task when approached from an analytical point of view due to the large number of sources and their heterogeneous nature. The use of simulation tools allows this task to be undertaken and using different hypotheses in less time and at a reasonable cost. This article presents the results obtained, in terms of quality of communications, for a Smart-Hospital with an arbitrary collection of heterogeneous services connected by Metro-Ethernet access. The results obtained: loss of information, delays and jitter will be used to outline the capacities to be contracted from the telecommunications supplier.

In massive machine-type communications (mMTC), an immense number of wireless devices communicate autonomously to provide users with ubiquitous access to information and services. The current 4G LTE-A cellular system and its Internet of Things (IoT) implementation, the narrowband IoT (NB-IoT), present appealing options for the interconnection of these wireless devices. However, severe congestion may arise whenever a massive number of highly-synchronized access requests occur. Consequently, access control schemes, such as the access class barring (ACB), have become a major research topic. In the latter, the precise selection of the barring parameters in a real-time fashion is needed to maximize performance, but is hindered by numerous characteristics and limitations of the current cellular systems. In this paper, we present a novel ACB configuration (ACBC) scheme that can be directly implemented at the cellular base stations. In our ACBC scheme, we calculate the ratio of idle to total available resources, which then serves as the input to an adaptive filtering algorithm. The main objective of the latter is to enhance the selection of the barring parameters by reducing the effect of the inherent randomness of the system. Results show that our ACBC scheme greatly enhances the performance of the system during periods of high congestion. In addition, the increase in the access delay during periods of light traffic load is minimal.

Ultrasonic measurements using orthogonal collimated beams provide both complementary and redundant information about internal parts of pieces or structures being tested, which must be fused. In this paper, a new wavelet-based digital processing technique which fuses ultrasonic pulse-echo traces obtained from several transducers located in two perpendicularly-coupled arrays is proposed. This is applied to accurately visualize the location of a small internal reflector by means of two dimensional (2D) displays. A-scans are processed in wavelet domain and fused in a common 2D pattern. A mathematical expression of the resulting 2D signal-to-noise ratio (SNR) is derived, and its accuracy is confirmed using benchmark tests performed with simulated registers and real measurements acquired using a multi-channel laboratory prototype. The measurement system consists of two properly-coupled perpendicular arrays comprising 4 square pulsed transducers and electronic driving circuitry. This technique improves 2D-SNR by a factor of twice the number of bands. In addition, good reflector location is obtained, since sub-millimeter 2D resolutions are achieved, despite only requiring eight ultrasonic channels. This good performance is confirmed by comparing the new wavelet fusing method with the two previously described techniques.

Denoising of biomedical signals using wavelet transform is a widely used technique. The use of undecimated wavelet transform (UWT) assures better denoising results but implies a higher complexity than discrete wavelet transform (DWT). Some implementation schemes have been proposed to perform UWT, one of them is Cycle Spinning (CS). CS is performed using the DWT of several circular shifted versions of the signal to analyse. The reduction of the number of shifted versions of the biomedical signal during denoising process used is addressed in the present work. This paper is about a variant of CS with a reduced number of shifts, called Partial Cycle Spinning (PCS), applied to ultrasonic trace denoising. The influence of the choice of PCS shifts in the denoised registers quality is studied. Several shifts selection rules are proposed, compared and evaluated. Denoising results over a set of ultrasonic registers are provided for PCS with different shift selection rules, CS and DWT. The work shows that PCS with the appropriate choice of shifts could be the best option to denoise biomedical ultrasonic traces.