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24622. Network optimisation using linear programming and genetic algorithm
- Creator:
- Sadegheih, A. and Drake, P. R.
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- linear programming, genetic algorithm, network optimisation, shortest path problem, transportation problem, and maximum flow problem
- Language:
- English
- Description:
- The problem of network is formulated as linear programming and genetic algorithm in spreadsheet model. GA’s are based in concept on natural genetic and evolutionary mechanisms working on populations of solutions in contrast to other search techniques that work on a single solution. An example application is presented. An empirical analysis of the effects of the algorithm’s parameters is also Presented in the context of this novel application.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
24623. Networking the Bloc :
- Creator:
- Kemp-Welch, Klara
- Type:
- text and monografie
- Subject:
- Umění, dějiny umění, umění moderní, umění experimentální, vztahy kulturní, světové dějiny od r. 1945 do současnosti, Československo 1945-1992, and dějiny umění, mecenát
- Language:
- English
- Rights:
- unknown
24624. Networks, Horizons, Centres and Hierarchies: On the Challenges of Writing on Modernism in Central Europe /
- Creator:
- Rampley, Matthew
- Type:
- text and studie
- Subject:
- Umění, dějiny umění, modernismus, metodologie, teorie umění, světové dějiny od r. 1918 do současnosti, and dějiny umění, mecenát
- Language:
- English
- Description:
- Sítě, horizonty, centra a hierarchie: výzvy psaní o modernismu ve střední Evropě.
- Rights:
- unknown
24625. Neural classifiers for schizophrenia diagnostic support on diffusion imaging data
- Creator:
- Savio, Alexandre, Charpentier, Juliette, Termenón , Maite, Shinn, Ann K., and Grana, Manuel
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- DWI, schizofrenia, neural classifiers, fractional anisotropy, and mean diffusivity
- Language:
- English
- Description:
- Diagnostic support for psychiatric disorders is a very interesting goal because of the lack of biological markers with sufficient sensitivity and specificity in psychiatry. The approach consists of a feature extraction process based on the results of Pearson correlation of known measures of white matter integrity obtained from diffusion weighted images: fractional anisotropy (FA) and mean diffusivity (MD), followed by a classification step performed by statistical support vector machines (SVM), different implementations of artificial neural networks (ANN) and learn vector quantization (LVQ) classifiers. The most discriminant voxels were found in frontal and temporal white matter. A total of 100% classification accuracy was achieved in almost every case, although the features extracted from the FA data yielded the best results. The study has been performed on publicly available diffusion weighted images of 20 male subjects.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
24626. Neural complexity and dissociation within the framework of quantum theory
- Creator:
- Bob, Petr and Faber, Josef
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- quantum computation, parallel distributed processing, complexity, and dissociation
- Language:
- English
- Description:
- In paper connections among dissociation, neural and EEG complexity are presented. They implicate the EEG correlate for dissociated rnental representations of neural assemblies which actually act in the brain-mind system. As a consequence of dissociation among these rnental representations biirst EEG activity is present. Burst activity is explained as a consequence of deterrninistic chaos, which leads to emerging of the underlying order of attractors in brain physiology. This chaos is comparable to the world of possibilities and their collapse in quanturn theory. The chaos may thus serve to link quanturn events to globál brain dyriamics and rriay be connected to the quanturn superposition of brain States and the collapse.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
24627. Neural connectivity of the amygdala in the human brain: A diffusion tensor imaging study
- Creator:
- Jang, Sung Ho and Kwon , Hyeok Gyu
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Amygdala, neural connectivity, diffusin tensor imaging, emotion, and memory
- Language:
- English
- Description:
- Several diffusion tensor imaging (DTI) studies have reported on the anatomical neural tracts between the amygdala and specific brain regions. However, no study on the neural connectivity of the amygdala has been reported. In the current study, using probabilistic DTI tractography, we attempted to investigate the neural connectivity of the amygdala in normal subjects. Forty eight healthy subjects were recruited for this study. A seed region of interest was drawn at the amygdala using the FMRIB Software Library based on probabilistic DTI tractography. Connectivity was defined as the incidence of connection between the amygdala and each brain region at the threshold of 1 and 5 streamlines. The amygdala showed 100% connectivity to the hippocampus, thalamus, hypothalamus, and medial temporal cortex regardless of the thresholds. In contrast, regarding the thresholds of 1 and 5 streamlines, the amygdala showed high conncetivity (over 60%) to the globus pallidus (100% and 92.7%), brainstem (83.3% and 78.1%), putamen (72.9% and 63.5%), occipito-temporal cortex (72.9% and 67.7%), orbitofrontal cortex (70.8 and 43.8%), caudate nucleus (63.5% and 45.8%), and ventromedial prefrontal cortex (63.5% and 31.3%), respectively. The amygdala showed high connectivity to the hippocampus, thalamus, hypothalamus, medial temporal cortex, basal ganglia, brainstem, occipito-temporal cortex, orbitofrontal cortex, and ventromedial prefrontal cortex. We believe that the methods and results of this study provide useful information to clinicians and researchers studying the amygdala.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
24628. Neural differentiation of pluripotent mouse embryonal carcinoma cells by retinoic acid: inhibitory effect of serum
- Creator:
- Pacherník, J., Bryja, V., Ešner, M., Kubala , L., Dvořák, P., and Hampl , A.
- Type:
- article, model:article, and TEXT
- Subject:
- Neural differentiation, Embryonal carcinoma cells, and Retinoic acid
- Language:
- English
- Description:
- In both embryonal carcinoma (EC) and embryonic stem (ES) cells, the differentiation pathway entered after treatment with retinoic acid (RA) varies as it is based upon different conditions of culture. This study employs mouse EC cells P19 to investigate the effects of serum on RA-induced neural differentiation occurring in a simplified monolayer culture. Cell morphology and expression of lineage-specific molecular markers document that, while non-neural cell types arise after treatment with RA under serum-containing conditions, in chemically defined serum-free media RA induces massive neural differentiation in concentrations of 10-9 M and higher. Moreover, not only neural (Mash-1) and neuroectodermal (Pax-6), but also endodermal (GATA-4, α-fetoprotein) genes are expressed at early stages of differentiation driven by RA under serum-free conditions. Furthermore, as determined by the luciferase reporter assay, the presence or absence of the serum does not affect the activity of the retinoic acid response element (RARE). Thus, mouse EC cells are able to produce neural cells upon exposure to RA even without culture in three-dimensional embryoid bodies (EBs). However, in contrast to standard EBs-involving protocol(s), neural differentiation in monolayer only takes place when complex signaling from serum factors is avoided. This simple and efficient strategy is proposed to serve as a basis for neurodifferentiation studies in vitro.
- Rights:
- http://creativecommons.org/licenses/by-nc-sa/4.0/ and policy:public
24629. Neural nets and normal forms from fuzzy logic point of view
- Creator:
- Perfilieva, I.
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- disjunctive, conjunctive and additive normal forms, BL-logic, Łukasiewicz logic, ŁII logic, fuzzy logic, fuzzy relation, and approximation
- Language:
- English
- Description:
- The paper addresses the problém of efficient and adequate representation of functions using two soft computing techniques: fuzzy logic and neural networks. The principle approach to the construction of approximating formulas is discussed. We suggest a generalized definition of the normál forms in predicate BL and ŁII logic and prove conditional equivalence between a formula and each of its normal forms. Some mutual relations between the normál forms will be also established.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
24630. Neural network approaches for predictive vector quantization of an image
- Creator:
- Mihalík, Ján and Labovský, Rostislav
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- neural network, vector quantization, vector prediction, Kohonen selforganization feature maps, clustering algoritlmi, and multilayer perceptron
- Language:
- English
- Description:
- The paper deals with a predictive vector quantization of an image based on a neural network architectures, wliere a vector predictor is iniplernented by three-layer neural network with various hidden nodes and bias units, sigrnoid function as nonlinearity and where vector quantizer is inipleinented by Kohonen self-organizing feature maps, it means the codebook is obtained by neural network clustering algorithm. We have tested aíi influence of a nuinber of hidden nodes, various convergention rates of a learning algorithm and a presence of the sigrnoid function to a rnean square prediction error. Next we háve studied an influence of codebook size to a rnean sciuare quantization error, that means a performance of predictive vector quantization system for various bit rates. The image of Lena of size 512 X 512 pels was coded for various bit rates, where we háve ušed onedirnensional and two-dimensional vector prediction of the blocks of pels.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public