Fuchs and collaborators [1, 2] showed that when a high voltage is applied between two electrodes, immersed in two beakers containing twice distilled water, a water bridge between the two containers is formed. We observed that a copper ions flow can pass through the bridge if the negative electrode is a copper electrode. The direction of the flux is not only depending on the direction of the applied electrostatic field but on the relative electronegativity of the electrodes too. The fact seems to suggest new perspectives in understanding the structure of water and the mechanisms concerning the arising of ions fluxes in living matter.
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
Cell-mediated immunity (CMI) response of healthy humans and cancer (Ca) patients to specific tumor antigen and nonspecific (LDV - lactate dehydrogenase virus) antigen, and of acute myocardial infarction (AMI) and schizophrenia (Sch) patients to nonspecific antigen was investigated. Large differences of CMI response of healthy humans in comparison with Ca, AMI, Sch patients were found. CMI response to antigens displays transferred information about cells under immune surveillance. LDV disturbs the oxidative energy production system. We assume that CMI response to LDV antigen monitors pathological states of mitochondrial energy production which results in disturbances of electromagnetic activity of living cells.
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
...-oriented infrastructure such as Hsinchu Science-based Industry Park (Hsu 2004) and research instit... world's 50 million annual shipments of computer notebooks are produced by four Taiwanese firms" (Y...
The centre of a communications network is a vertex set. The distances between every vertex in the centre set and all other vertices of the network are minimal. In some cases, the centre of the network can be a path, which includes a desired number of vertices. This centre is called a path centre of the network. In this paper, we aim to find a path centre of a given network with the needed number of vertices. We give the distance measures of the network and represent an algorithm searching the path centre of the network.
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
The Self-Organizing Map (SOM) is a popular unsupervised neural network able to provide effective clustering and data visualization for data represented in multidimensional input spaces. In this paper, we describe Fast Learning SOM (FLSOM) which adopts a learning algorithm that improves the performance of the standard SOM with respect to the convergence time in the training phase. We show that FLSOM also improves the quality of the map by providing better clustering quality and topology preservation of multidimensional input data. Several tests have been carried out on different multidimensional datasets, which demonstrate better performances of the algorithm in comparison with the original SOM.
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
... very excited by this particular field of science, coming to understand the wide-open space, which w... in this area in the Institute of Computer Science (ICS) of the then Czechoslovak Academy of ...
We consider the problem of separating noisy overcomplete sources from linear mixtures, i.e., we observe N mixtures of M > N sparse sources. We show that the "Sparse Coding Neural Gas" (SCNG) algorithm [8, 9] can be employed in order to estimate the mixing matrix. Based on the learned mixing matrix the sources are obtained by orthogonal matching pursuit. Using synthetically generated data, we evaluate the influence of (i) the coherence of the mixing matrix, (ii) the noise level, and (iii) the sparseness of the sources with respect to the performance that can be achieved on the representation level. Our results show that if the coherence of the mixing matrix and the noise level are sufficiently small and the underlying sources are sufficiently sparse, the sources can be estimated from ...
...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
Tracking moving objects is a vital visual task for the survival of an animal. We describe oscillatory neural network models of visual attention with a central element that can track a moving target among a set of distracters on the screen. At the initial stage, the model forms the focus of attention on an arbitrary object that is considered as a target. Other objects are treated as distracters. We present here two models: 1) synchronisation based model designed as a network of phase oscillators and 2) spiking neural model which is based on the idea of resource-limited parallel visual pointers. Selective attention and the tracking process are represented by the partial synchronisation between the central unit and a subgroup of peripheral elements. Simulation results are in overall agreem...
... and by the Ministry of High Education and Science of the Russian Federation (Grant 2.1.1/3876). Copyyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights R...
This paper proposes an endogenous human resources selection process by using linguistic information from a competency management perspective. We consider different sets of appraisers taking part in the evaluation process, having a different knowledge about the candidates that are being evaluated. Then, appraisers can express their assessments in different linguistic domains according to their knowledge. The proposed method converts each linguistic label into a fuzzy set on a common domain. Candidates are ranked by using different aggregation operators in order to allow the management team to make a final decision.
... by the Spanish Ministry of Education and Science grant SEJ2006-04267/ECON, Junta de Castilla y Leó...Copyright Institute of Computer Science 2010Provided by ProQuest LLC. All Rights R...
Artificial Neural Networks are commonly used in pattern classification, function approximation, optimization, pattern matching, machine learning and associative memories. They are currently being an alternative to traditional statistical methods for mining data sets in order to classify data. Artificial Neural Networks are well-established technology for solving prediction and classification problems, using training and testing data to build a model. However, the success of the networks is highly dependent on the performance of the training process and hence the training algorithm. In this paper, we applied the Artificial Bee Colony (ABC) Optimization Algorithm on training feed-forward neural networks to classify different data sets which are widely used in the machine learning communit...
..., robotic control, signal processing, computer vision and many other problems that fall under the...Copyright Institute of Computer Science 2009Provided by ProQuest LLC. All Rights Reserved....
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