Intrinsic spin noise in MgO magnetic tunnel junctions

We consider two intrinsic sources of noise in ultra-sensitive magnetic field sensors based on MgO magnetic tunnel junctions, coming both from 25 Mg nuclear spins (I = 5/2, 10% natural abundance) and S = 1 Mg-vacancies. While nuclear spins induce noise peaked in the MHz frequency range, the vacancies noise peaks in the GHz range. We find that the nuclear noise in submicron devices has a similar magnitude than the 1/f noise, while the vacancy-induced noise dominates in the GHz range. Interestingly, the noise spectrum under a finite magnetic field gradient may provide spatial information about the spins in the MgO layer.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

Influence of using slag cement on the microstructure and durability related properties of cement grouts for micropiles

Today, the use of micropiles for different applications has become very common. In Spain, the cement grouts for micropiles are prepared using ordinary Portland cement and w:c ratio 0.5, although the micropiles standards do not restrict the cement type to use, provided that it reaches a certain compressive strength. In this study, the influence of using slag cement on the microstructure and durability related properties of cement grouts for micropiles have been studied until 90 hardening days, compared to an ordinary Portland cement. Finally, slag cement grouts showed good service properties, better than ordinary Portland cement ones.

Noise-tolerance feasibility for restricted-domain Information Retrieval systems

Information Retrieval systems normally have to work with rather heterogeneous sources, such as Web sites or documents from Optical Character Recognition tools. The correct conversion of these sources into flat text files is not a trivial task since noise may easily be introduced as a result of spelling or typeset errors. Interestingly, this is not a great drawback when the size of the corpus is sufficiently large, since redundancy helps to overcome noise problems. However, noise becomes a serious problem in restricted-domain Information Retrieval specially when the corpus is small and has little or no redundancy. This paper devises an approach which adds noise-tolerance to Information Retrieval systems. A set of experiments carried out in the agricultural domain proves the effectiveness of the approach presented.

Impedance spectroscopy study of the effect of environmental conditions in the microstructure development of OPC and slag cement mortars

In this work, the microstructure of mortars made with an ordinary Portland cement and slag cement has been studied. These mortars were exposed to four different constant temperature and relative humidity environments during a 180-day period. The microstructure has been studied using impedance spectroscopy, and mercury intrusion porosimetry as a contrast technique. The impedance spectroscopy parameters make it possible to analyze the evolution of the solid fraction formation for the studied mortars and their results are confirmed with those obtained using mercury intrusion porosimetry. The development of the pore network of mortars is affected by the environment. However, slag cement mortars are more influenced by temperature while the relative humidity has a greater influence on the OPC mortars. The results show that slag cement mortars hardened under non-optimal environments have a more refined microstructure than OPC mortars for the studied environmental conditions.