Low bit depth representation motion estimation algorithms: a comparative study

A comparative study of low complexity motion estimation algorithms is presented. The algorithms included in the study are the 1-bit transform, the 2-bit transform, the constrained 1-bit transform and the multiplication free 1-bit transform which are using different motion estimation strategies compared to standard exhaustive search algorithm-mean absolute difference or similar combinations. These techniques provide better performance in terms of computational load compared to traditional algorithms. Although the accuracy of motion compensation is only slightly lower comparing to the other techniques, results in terms of objective quality (peak signal-to-noise ratio) and entropy are comparable. This fact, nominates them as suitable candidates for inclusion in embedded devices applications where lower complexity translates to lower power consumption and consequently improved device autonomy.     

A fuzzy evolutionary framework for combining ensembles

We propose an evolutionary framework for the production of fuzzy rule bases where each rule executes an ensemble of predictors. The architecture, the rule base and the composition of the ensembles are evolved over time. To achieve this, we employ a context-free grammar within a hybrid genetic programming system using a multi-population model. As base predictors, multilayer perceptron neural networks and support vector machines are available. We apply the system to several function approximation and regression tasks and compare the results with recent research and state-of-the-art models. We conclude that the proposed architecture is competitive and has a number of very desirable features supporting automation of predictive model building and their adaptation over time. Finally, we suggest further potential research directions.     

Investigation of isolated thunderstorms lightning activity over eastern Mediterranean using Meteosat rapid scan infrared imagery

An analysis of selected spatiotemporal characteristics of isolated thunderstorms in relation to cloud-to-ground (CG) lightning over part of the eastern Mediterranean is performed. The purpose of the study is twofold: to better understand and improve the basic knowledge of the physical mechanisms of the phenomenon and to offer new means of nowcasting the lightning activity in such thunderstorms. Meteosat Second Generation (MSG) Rapid Scan Service (RSS) infrared imagery which offers the option of tracking the examined storms with a time frequency of 5 minutes is one of the two utilized datasets, the other being ZEUS very low frequency (VLF) lightning detection system’s CG discharge data. It was shown that a cloud top temperature of about ?20°C is required for the onset of lightning activity. A rapid drop of the cloud-top temperature of about 11°C in 5 minutes on average is observed a few minutes before or during lightning initiation. The maximization of the activity is usually quite close to the overall minimum cloud-top temperature of the cell. A temperature increase of 3.5°C from this overall minimum can mark the end of the activity, which is also associated to the time evolution of the cell’s horizontal extent. In fact, after the cell’s horizontal area stops to increase and/or starts to gradually diminish, CG lightning activity is expected to stop.     

Towards an ICT-based psychology: E-psychology

Cognitive science is the scientific domain which studies, analyzes, simulates and infers for various aspects, functions and procedures of human mentality such as, thinking, logic, language, knowledge, memory, learning, perception and the ability to solve problems. E-psychology is in close relation with the cognitive science domain, but expands beyond it, as e-psychology is the efficient convergence of psychology and Information and Communication Technologies (ICTs). E-psychology offers a number of services such as supporting, diagnosis, assessment, therapy, counseling, intervention and tests through an effective exploitation of ICTs. This article presents a user-friendly, flexible and adaptive electronic platform, which supports both synchronous and asynchronous e-psychology activities through the use of informative and communicative tools and services, which can be adapted to support various methods of e-psychology activities. It is important to underline that e-psychology is not an alternative psychology field, but a resource to enhance the conventional psychology process.     

Analysis and performance evaluation of a pilot-aided interpolated channel estimator for OFDM systems

In this paper, we propose a novel pilot-aided channel estimator through interpolation for Orthogonal Frequency Division Multiplexing (OFDM) systems that replaces part of the virtual subcarriers with pilot subcarriers (pilots) reducing the interpolation error while keeping the code rate stable. A novel thorough analysis of the Mean Square Error (MSE) of the proposed estimator is given for the general case where data subcarriers are positioned before the first and after the last pilot. Simulations show the improvement of the proposed scheme in MSE and Bit Error Rate (BER) when applied to a practical OFDM wireless local area network type of system with realistic channel conditions.     

A rapid microwave-assisted derivatization process for the determination of phenolic acids in brewer’s spent grains

A simple and fast method for the TMS derivatization of phenolic acids in a closed vial using microwave irradiation followed by GC/MS analysis is proposed. A full factorial design was used to investigate the effects of two independent variables, namely, time and power of microwave irradiation, on the yield of silylation reaction. The optimal conditions were tested against the classical heating derivatization procedure. No significant differences were found between the classical heating and microwave-assisted derivatization. Chromatographic separation of the nine phenolic acids examined was achieved in 16 min. The mass spectral fragmentation patterns of the derivatives obtained by the proposed method were identical to those from the classical heating. Four different batches of brewer’s spent grain were extracted and analyzed for the total phenolic acid content. Significant differences between the batches of spent grains were found for all analytes. The total phenolic acid content varied between 2688 and 4884 μg/g.     

Sensory characteristics and iron dialyzability of gluten-free bread fortified with iron

The objectives of the present study were (a) to produce gluten-free bread, fortified with iron (GFB-Fe), using selected iron compounds (ferric pyrophosphate, ferric pyrophosphate with emulsifiers, NaFeEDTA, electrolytic iron, ferrous gluconate, ferrous lactate and ferrous sulphate) (b) to test sensory characteristics of the GFB-Fe (feel-mouth texture, crumb colour, aroma and taste) (c) to compare iron dialyzability of various iron compounds in GFB-Fe. The most acceptable products were those fortified with ferric pyrophosphate with emulsifiers and ferric pyrophosphate. Ferrous dialyzable iron (ferrous iron with molecular weight lower than 8000 Da, an index for prediction of iron bioavailability) was measured under simulated gastrointestinal conditions. Ferrous dialyzable iron in GFB-Fe fortified with ferric pyrophosphate with emulsifiers, NaFeEDTA, ferrous bis-glycinate, ferrous gluconate or ferrous sulphate was higher than that in GFB-Fe fortified with electrolytic iron, ferrous lactate or ferric pyrophosphate (P < 0.05). These results are promising for the development of GFB-Fe products in the future.     

Finding all roots of 2?×?2 nonlinear algebraic systems using back-propagation neural networks

The objective of this research is the numerical estimation of the roots of a complete 2?×?2 nonlinear algebraic system of polynomial equations using a feed forward back-propagation neural network. The main advantage of this approach is the simple solution of the system, by building a structure—including product units—that simulates exactly the nonlinear system under consideration and find its roots via the classical back-propagation approach. Examples of systems with four or multiple roots were used, in order to test the speed of convergence and the accuracy of the training algorithm. Experimental results produced by the network were compared with their theoretical values.