993 resultados para correlation pattern


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F-4 generation of human growth hormone (hGH) gene-transgenic red common carp, and the non-transgenic controls were fed for 8 weeks on purified diets with 20%, 30% or 40% protein. Analysis of whole-body amino acids showed that the proportions of lysine, leucine, phenylalanine, valine and alanine, as percentages of body protein, increased significantly, while those of arginine, glutamic acid and tyrosine decreased, with increases in dietary protein level in at least one strain of fish. Proportions of the other amino acids were unaffected by the diets. The proportions of lysine and arginine were significantly higher, while those of leucine and alanine were lower in the transgenics than in the controls in at least one diet group. Proportions of the other amino acids were unaffected by strain. The results suggest that the whole-body amino acid profile of transgenic carp, when expressed as proportions of body protein, was in general, similar to that of the non-transgenic controls. (C) 2000 Elsevier Science B.V. All rights reserved.

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The spatial pattern of the small fish community was studied seasonally in 1996 in the Biandantang Lake. Based on plant cover, the lake was divided into five habitats, arranged in the order by plant structure complexity from complex to simple: Vallisneria spiralis habitat (V habitat), Vallisneria spiralis-Myriophyllum spicatum habitat (V-M habitat), Myriophyllum spicatum habitat (M habitat), Nelunbo nucefera habitat (N habitat), and no vegetation habitat (NV habitat). A modified popnet was used for quantitative sampling of small fishes. A total of 16 fish species were collected; Hypseleotris swinhonis, Ctenogobius giurinus, Pseudorasbora parva, Carassius auratus and Paracheilognathus imberis were the five numerically dominant species. In both summer and autumn, the total density of small fishes was about 10 ind m(-2). Generally, Ctenogobius giurinus, a sedatory, benthic fish, was distributed more or less evenly among the five habitats, while the other four species had lower densities in the N habitat and NV habitat, which had the simplest structures. The distribution of the small fish species showed seasonal variations. In winter, most species concentrated in the V habitat, which had the most complex structure. In spring, the fish had low densities in the N and NV habitat, and were more or less evenly distributed in the other habitats. In summer, the fish had a low density in the NV habitat, and were evenly distributed in the other habitats. In autumn, the fish had higher densities in the V-M and M habitats than in the others. Generally, spatial overlaps between the dominant species were higher in winter than in the other seasons. It was suggested that the variations in the importance of predation risk and resource competition in habitat choice determined the seasonal changes of spatial patterns in the small fishes in the Biandantang Lake.

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Sediments and soils collected from the Ya-Er Lake area in China were analysed for the polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs), polychlorinated biphenyl (PCBs), hexachlorocyclohexane (HCHs) and hexachlorobenzene (HCB). The results indicated the main pollution problems in the Ya-Er Lake area, which was heavily polluted by HCHs and chlorobenzenes, now is dominantly polluted by PCDD/Fs, PCBs and HCB. The occurrence of PCDD/Fs and PCBs with relatively high levels of HpCDDs, OCDD and low chlorinated-substituted PCBs, is attributed to the discharge of waste water and biodegradation. The vertical distributions of HCH-residues are related with the content of organic carbon and particle size. Copyright (C) 1996 Elsevier Science Ltd

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In this paper, a new classifier of speaker identification has been proposed, which is based on Biomimetic pattern recognition (BPR). Distinguished from traditional speaker recognition methods, such as DWT, HMM, GMM, SVM and so on, the proposed classifier is constructed by some finite sub-space which is reasonable covering of the points in high dimensional space according to distributing characteristic of speech feature points. It has been used in the system of speaker identification. Experiment results show that better effect could be obtained especially with lesser samples. Furthermore, the proposed classifier employs a much simpler modeling structure as compared to the GMM. In addition, the basic idea "cognition" of Biomimetic pattern recognition (BPR) results in no requirement of retraining the old system for enrolling new speakers.

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Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.

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Biomimetic pattern recogntion (BPR), which is based on "cognition" instead of "classification", is much closer to the function of human being. The basis of BPR is the Principle of homology-continuity (PHC), which means the difference between two samples of the same class must be gradually changed. The aim of BPR is to find an optimal covering in the feature space, which emphasizes the "similarity" among homologous group members, rather than "division" in traditional pattern recognition. Some applications of BPR are surveyed, in which the results of BPR are much better than the results of Support Vector Machine. A novel neuron model, Hyper sausage neuron (HSN), is shown as a kind of covering units in BPR. The mathematical description of HSN is given and the 2-dimensional discriminant boundary of HSN is shown. In two special cases, in which samples are distributed in a line segment and a circle, both the HSN networks and RBF networks are used for covering. The results show that HSN networks act better than RBF networks in generalization, especially for small sample set, which are consonant with the results of the applications of BPR. And a brief explanation of the HSN networks' advantages in covering general distributed samples is also given.

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Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.

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Erbium-doped hydrogenated amorphous silicon suboxide films containing silicon clusters (a-SiOx:H) were prepared. The samples exhibited photoluminescence (PL) peaks at around 750nm and 1.54 mu m, which could be assigned to the electron-hole recombination in silicon clusters and the intra-4f transition in Er3+, respectively. We compared annealing behaviors of Si clusters and Er3+ emission and found that Si clusters emission depends strongly upon crystallinity of Si clusters, whereas Er3+ emission is not sensitive to whether it is Si nanocrystals (nc-Si) or amorphous Si (a-Si) clusters. The erbium-doped a-SiOx:H films containing either a-Si clusters or nc-Si have the same kind of Er3+ -emitting centers. Based on these results, it is concluded that a-Si clusters can play the same role on Er3+ excitation as nc-Si. (c) 2004 Elsevier B.V. All rights reserved.

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We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

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We have observed the weak antilocalization (WAL) and beating SdH oscillation through magnetotransport measurements performed on a heavily delta-doped In0.52Al0.48As/In0.53Ga0.47As/In0.5Al0.48As single quantum well in an applied magnetic field up to 13 T and a temperature at 1.5 K. Both effects are caused by the strong Rashba spin-orbit (SO) coupling due to high structure inversion asymmetry (SIA). The Rashba SO coupling constant alpha and zerotield spin splitting Delta(0) are estimated and the obtained values are consistent from different analysis for this sample. (c) 2007 Elsevier Ltd. All rights reserved.

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The tin-doped indium oxide (ITO) thin films were prepared by reactive thermal evaporation on the glass substrates. The effects of substrate temperatures (T-s) on the grain preferred orientation, the electrical and optical properties of ITO films were studied. X-ray diffraction (XRD) patterns indicated that the preferred orientation of film changes from (222) to (400) as T, > 200 degrees C. It can be explained by that the low-index crystallographic planes are easier to be formed when the adatoms have high surface mobility. The Hall measurements indicated that both the concentration and mobility of carrier increase with increasing T,,,. The grain orientation of film does not influence the transmissivity and the carrier concentration, but enhances the carrier mobility. The transmissivity of ITO films is over 90% in the visible wavelength region (except that of the film deposited at 125 degrees C). A minimum resistivity of 5 X 10-4 Omega cm is achieved for the (400) preferred orientation film. Thus, the highest figure of merit of 3.5 x 10(-2) square/Omega is obtained for the film with (400) preferred orientation. The correlation between the preferred orientation and electrical and optical properties are discussed.

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Using time-resolved photoluminescence and time-resolved Kerr rotation spectroscopy, we explore the unique electron spin behavior in an InAs submonolayer sandwiched in a GaAs matrix, which shows very different spin characteristics under resonant and non-resonant excitations. While a very long spin relaxation lifetime of a few nanoseconds at low temperature is observed under non-resonant excitation, it decreases dramatically under resonant excitation. These interesting results are attributed to the difference in electron-hole interactions caused by non-geminate or geminate capture of photo-generated electron-hole pairs in the two excitation cases, and provide a direct verification of the electron-hole spatial correlation effect on electron spin relaxation. (c) 2007 Elsevier Ltd. All rights reserved.

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For both, (Al,Ga)N with low Al content grown on a GaN nucleation layer and (AI,Ga)N with high Al content gown on an AlN nucleation layer, the inhomogeneous distribution of the luminescence is linked to the distribution of defects, which may be due to inversion domains. In the former system, defect regions exhibit a much lower Al content than the nominal one leading to a splitting of the respective luminescence spectra. In the latter system, a domain-like growth is observed with a pyramidal surface morphology and non-radiative recombination within the domain boundaries. (c) 2007 WILEYNCH Verlag GmbH & Co. KGaA, Weinheim.

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Based on biomimetic pattern recognition theory, we proposed a novel speaker-independent continuous speech keyword-spotting algorithm. Without endpoint detection and division, we can get the minimum distance curve between continuous speech samples and every keyword-training net through the dynamic searching to the feature-extracted continuous speech. Then we can count the number of the keywords by investigating the vale-value and the numbers of the vales in the curve. Experiments of small vocabulary continuous speech with various speaking rate have got good recognition results and proved the validity of the algorithm.