Validation of radiotracer technology in dynamic scaling experiments in porous media

The present study attempts to qualify the radiotracer technology as a reliable source of information for laboratory experimental investigations of the scaling phenomena involved in geological systems. The critical information provided by these experiments is the induction time of scaling and the profile of the scale deposition along the deposition medium.A series of calcite scaling experiments in sandpacks were carried out. In these experiments, ⁴⁷Ca²⁺ was used as tracer to monitor the CaCO₃ precipitation. The results show that the introduction of the tracer technology, for the first time in scaling experiments in porous media, has been successful and will constitute a valuable tool in further studies of the scaling mechanism in geological formations. The advantages of the radioactive tracer technology are its high sensitivity for the onset of precipitation (short induction time) and its ability to visualize the scale distribution as a function of time.     

Visual tracking using the Earth Mover's Distance between Gaussian mixtures and Kalman filtering

In this paper, we demonstrate how the differential Earth Mover's Distance (EMD) may be used for visual tracking in synergy with Gaussian mixtures models (GMM). According to our model, motion between adjacent frames results in variations of the mixing proportions of the Gaussian components representing the object to be tracked. These variations are computed in closed form by minimizing the differential EMD between Gaussian mixtures, yielding a very fast algorithm with high accuracy, without recurring to the EM algorithm in each frame. Moreover, we also propose a framework to handle occlusions, where the prediction for the object's location is forwarded to an adaptive Kalman filter whose parameters are estimated on line by the motion model already observed. Experimental results show significant improvement in tracking performance in the presence of occlusion.     

Techno-economic analysis of RES & hydrogen technologies integration in remote island power system

The main objective of the present study is the integration of hydrogen technologies as an energy storage medium in a hybrid power system. The existing power system of the island of Milos, which is based on fossil fuel generators and a small wind park, is assessed in the context of this paper. System level simulation results, from both technical and economic point of view, are presented for the currently existing and the proposed island's hybrid power system. The latter integrates a higher number of wind turbines and hydrogen technologies as energy storage medium, and the two system architectures are being compared taking into account not only technical and economic parameters but also Green House – Gas (GHG) emissions, fossil fuels consumption and Renewable Energy Sources (RES) penetration increase. Moreover, a sensitivity analysis has been performed in order to determine the contribution of hydrogen technologies equipment costs; with the cost of energy produced (COE) being the critical parameter. Results show that COE for the proposed power system is higher than the existing one, but on the other hand GHG emissions and fossil fuel consumption are significantly reduced. In addition, RES penetration increases dramatically and the sensitivity analysis indicates that a further reduction in hydrogen technologies equipment and subsidy on wind turbine costs would make RES & Hydrogen-based systems economically competitive to the existing power system of the island.     

The CHIRP II High-power Excimer Laser

Abstract

The current performance of the high-average-power CHIRP II excimer laser is described. A power of 430 W at 1100 pulses per second has been achieved on the XeCl excimer. Particular reference is made to the undesirable high-pulse-repetition-frequency effects observed in the testbed CHIRP I laser, and successfully avoided in CHIRP II.     

On acoustic emissions in percussion laser drilling

Laser drilling is a well established sheet metal processing method. The development of a monitoring system capable of assessing the dimensions of holes is the subject of this work. This paper investigates the applicability of an acoustic-based monitoring system for the percussion laser drilling process. Correlation between the sensor output and the hole's geometry, determined by its depth and upper diameter, is investigated and the results are presented. In general, the results indicate that a correlation exists between the acoustic signal output and the depth of the hole.     

Lactose uptake rate measurements by C-labelled lactose reveals promotional activity of porous cellulose in whey fermentation by kefir yeast

Lactose uptake rate by kefir yeast, immobilized on tubular cellulose and gluten pellets during fermentation of lactose and whey, was monitored using ¹⁴C-labelled lactose. Results illustrated that, in all cases, lactose uptake rate was strongly correlated with fermentation rate and the fermentation’s kinetic parameters were improved by kefir yeast entrapped in tubular cellulose. As a result, twofold faster fermentations were achieved in comparison with kefir yeast immobilized on gluten. This is probably due to cluster and hydrogen bonds formation between cellulose and inhibitors, such as Ca⁺⁺ and generated lactic acid, by which they leave the liquid medium. The findings, regarding the promotional effect of cellulose, seem promising for application in industrial whey fermentations.     

Reinforcement Learning Using the Stochastic Fuzzy Min–Max Neural Network

The fuzzy min–max neural network constitutes a neural architecture that is based on hyperbox fuzzy sets and can be incrementally trained by appropriately adjusting the number of hyperboxes and their corresponding volumes. An extension to this network has been proposed recently, that is based on the notion of random hyperboxes and is suitable for reinforcement learning problems with discrete action space. In this work, we elaborate further on the random hyperbox idea and propose the stochastic fuzzy min–max neural network, where each hyperbox is associated with a stochastic learning automaton. Experimental results using the pole balancing problem indicate that the employment of this model as an action selection network in reinforcement learning schemes leads to superior learning performance compared with the traditional approach where the multilayer perceptron is employed.     

Properties and hydration of blended cements with calcareous diatomite

In this paper the effect of diatomite addition on blended cement properties and hydration was studied. Calcareous diatomaceous rocks of Zakynthos Island, Ionian Sea, containing mainly CaCO₃ and amorphous silica of biogenic origin with the form of opal-A were used. Cement mortars and pastes, with 0%, 10%, 20% and 35% replacement of cement with the specific diatomite, were examined. Strength development, water demand and setting time were determined in all samples. In addition, XRD, SEM and weight loss at 350 °C were applied in order to study the hydration products and the hydration rate in the cement-diatomite pastes. Blended cements, having up to 10% diatomite content, develop the same compressive strength, as the corresponding Portland cement, while the presence of diatomite leads to an increase of the paste water demand. Diatomite is characterized as natural pozzolana, as it satisfies the requirements of EN 197 1 concerning the active silica content. The pozzolanic nature of the diatomite results to the formation of higher amounts of hydrated products, specifically at the age of 28 days.     

A class-adaptive spatially variant mixture model for image segmentation.

We propose a new approach for image segmentation based on a hierarchical and spatially variant mixture model. According to this model, the pixel labels are random variables and a smoothness prior is imposed on them. The main novelty of this work is a new family of smoothness priors for the label probabilities in spatially variant mixture models. These Gauss-Markov random field-based priors allow all their parameters to be estimated in closed form via the maximum a posteriori (MAP) estimation using the expectation-maximization methodology. Thus, it is possible to introduce priors with multiple parameters that adapt to different aspects of the data. Numerical experiments are presented where the proposed MAP algorithms were tested in various image segmentation scenarios. These experiments demonstrate that the proposed segmentation scheme compares favorably to both standard and previous spatially constrained mixture model-based segmentation.     

Effects of olive pomace and olive pomace oil on growth performance,fatty acid composition and cardio protective properties of gilthead sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax)

Gilthead sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax) were fed with two experimental diets: olive pomace diet and olive pomace oil diet, in order to examine whether fish oil substitution in fish feeds by olive oil production wastes, such as olive pomace and olive pomace oil, has an influence on growth performance, fatty acid composition and cardio protective properties of fish. Gilthead sea bream fed with both experimental diets exhibited satisfactory growth performance factors while sea bass did not. The total lipids of gilthead sea bream fed with olive pomace diet contained statistically decreased levels of fatty acids, while exhibited the most potent biological activity against platelet aggregation induced by Platelet Activating Factor. These data indicate that olive pomace can be used as a partial substitute of fish oil in fish feed improving its cardio protective properties.