The bonding structure and hydrogen content of amorphous hydrogenated silicon nitride (a-SiN x :H) thin films have been investigated by infrared spectroscopy and ion beam techniques. Electron cyclotron resonance plasma enhanced chemical vapor deposition was used to produce these films under different values of gas flow ratio, deposition temperature, and microwave power.The amount of bonded hydrogen was calculated from the N-H and Si-H infrared absorption bands. An increase of the SiH 4 partial pressure during deposition was found to have the same effect on the H content as an increase of the substrate temperature: both cause a decrease of the N-H bond density and an increase in the number of Si-H bonds. This is explained by a competitive process in the formation of N-H and Si-H bonds during the growth of the film, whereby Si-H bonds are favored at the expense of N-H bonds when either the SiH 4 flow or the substrate temperature are increased. Such tendency to chemical order is compared with previous results in which the same behavior was induced by thermal annealing or ion beam bombardment.
The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.
This paper proposes an all-hardware architecture to perform the subpixel refinement operation in the scale invariant transform algorithm. Although the literature describes several hardware implementations of this algorithm, due to its complexity, most of them are based on simplifications of it. These implementations normally exclude the subpixel refinement stage, which, however, is an essential process to obtain accurate results in image matching applications.The architecture has been described in very high-speed integrated circuit hardware description language at register transfer level and synthesized on a Xilinx Zynq 7020 device. The latency of the proposed architecture to generate a refinement operation is 211 clock cycles, and the throughput achieved exploiting pipeline techniques is 64 cycles. The architecture uses fixed-point data representation and has been tested with images from known databases, yielding very good performance compared with the floating-point software implementation of the algorithm.
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