Phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters

Analog Integrated Circuits and Signal Processing - This paper presents the complete design of a phase locked loop-based clock synthesizer for reconfigurable analog-to-digital converters. The...     

A novel ceramic matrix composite based on YNbO4–TiO2 for microwave applications

This work presents the dielectric properties of YNbO₄ (YNO)–TiO₂ composites in the microwave range. X-ray diffraction analysis demonstrates that the addition of TiO₂ to YNO results in the formation of a Y(Nb_0.5Ti_0.5)₂O₆ phase. In the microwave range, the values of permittivity and dielectric loss did not present major changes with the increment of TiO₂. Moreover, the addition of TiO₂ results in an improvement in the thermal stability of YNO, with YNO63 demonstrating a resonant frequency of ?8.96 ppm.°C^?1. We utilised numerical simulations to evaluate the behaviour of these materials as dielectric resonator antennae and it is found that they exhibit a reflection coefficient below ?10 dB at the resonant frequency, with a realised gain of 4.94 – 5.76 dBi, a bandwidth of 665–1050 MHz and a radiation efficiency above 84%. Our results indicate that YNO–TiO₂ composites are interesting candidates for microwave operating devices.     

Increasing the photocatalytic and fungicide activities of Ag3PO4 microcrystals under visible-light irradiation

The present study reports for the first time the performance of silver phosphate (Ag₃PO₄) microcrystals as photocatalyst (degradation of Rodamine B-RhB) and antifungal agent (against Candida albicans–C. albicans) under visible-light irradiation (455 nm). Ag₃PO₄ microcrystals were synthesized by a simple co-precipitation (CP) method at room temperature. The structural and electronic properties of the as-synthetized Ag₃PO₄ have been investigated before and after 4 cycles of RhB degradation under visible light using X-ray diffraction (XRD), micro-Raman spectroscopy, UV–Vis spectrophotometer and field emission scanning electron microscopy (FE-SEM) images. The antifungal activity was analyzed in planktonic cells and 48h-biofilm of C. albicans by colony forming units (CFU) counting, confocal laser and FE-SE microscopies. Statistical analysis was carried out using SPSS software. Morphological and structural modifications of Ag₃PO₄ were observed upon recycling. After 4 recycles, the material maintained its photodegradation property; an eightfold increase in the efficiency of Ag₃PO₄ was observed in planktonic cells and a two fold increase in biofilm when irradiated under visible light. Thus, higher antifungal effectiveness against C. albicans was obtained when associated with visible-light irradiation.     

Corrosion behavior of T24, T92, VM12, and AISI 304 steels exposed to KCl–NaCl–K2SO4–Na2SO4 salt mixtures

The corrosion mechanisms of T24, T92, VM12, and AISI 304 steels are studied under the influence of NaCl–KCl, NaCl–Na₂SO₄, and KCl–K₂SO₄ salt mixtures in a dry air atmosphere at 650°C for 15 days. NaCl–KCl was the most aggressive deposit and AISI 304 stainless steel exhibited the highest corrosion resistance. There was no relation between the Cr content of the ferritic steels and their corrosion resistance in NaCl–KCl. In contrast, the resistance of high-Cr steels was better when exposed to NaCl–Na₂SO₄ and KCl–K₂SO₄. The high-Cr and the low-Cr steels were more susceptible to NaCl–Na₂SO₄ and to KCl–K₂SO₄, respectively.     

Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Physicochemical and technological properties of beef burger as influenced by the addition of pea fibre

This study aimed to evaluate the physicochemical characteristics and sensory attributes of beef burgers with the addition of pea fibre as a partial substitute of meat or fat. Three formulations were prepared: control (CON) – similar to the commercial formulation; fibre/less meat (FLM)—5% meat reduction and addition of 1% pea fibre; fibre/less fat (FLF)—7% fat reduction and addition of 1% pea fibre. Non-significant differences were obtained for pH, colour parameters (L* and b*), texture profile, cooking loss and size reduction among formulations. Moreover, sensory analysis with consumers of beef burgers did not indicate differences among the formulations for all the analysed attributes. Therefore, pea fibre is a promising partial replacer for meat and fat in beef burgers due to the preservation of technological parameters and sensory acceptance.     

Ternary Blends of Renewable Fast Pyrolysis Bio-Oil,Advanced Bioethanol,and Marine Gasoil as Potential Marine Biofuel

An alternative for reducing emissions from marine fuel is to blend bio-oil from lignocellulose non-edible feedstocks to diesel fossil fuels. Phase diagrams of the ternary systems were built to represent the transition from heterogeneous regions to homogeneous regions. Four homogeneous blends of bio-oil of eucalyptus-bioethanol-marine gasoil were experimentally characterized with respect to the most important fuel parameters for marine engines: water content, flash point, low heating value, viscosity, and acidity. Blends with closer properties to marine gasoil replacement, lower costs, and environmental impacts should be tested for large engines.     

A self-adaptive synthetic over-sampling technique for imbalanced classification

Traditionally, in supervised machine learning, (a significant) part of the available data (usually 50%-80%) is used for training and the rest—for validation. In many problems, however, the data are highly imbalanced in regard to different classes or does not have good coverage of the feasible data space which, in turn, creates problems in validation and usage phase. In this paper, we propose a technique for synthesizing feasible and likely data to help balance the classes as well as to boost the performance in terms of confusion matrix as well as overall. The idea, in a nutshell, is to synthesize data samples in close vicinity to the actual data samples specifically for the less represented (minority) classes. This has also implications to the so-called fairness of machine learning. In this paper, we propose a specific method for synthesizing data in a way to balance the classes and boost the performance, especially of the minority classes. It is generic and can be applied to different base algorithms, for example, support vector machines, k-nearest neighbour classifiers deep neural, rule-based classifiers, decision trees, and so forth. The results demonstrated that (a) a significantly more balanced (and fair) classification results can be achieved and (b) that the overall performance as well as the performance per class measured by confusion matrix can be boosted. In addition, this approach can be very valuable for the cases when the number of actual available labelled data is small which itself is one of the problems of the contemporary machine learning.