Pattern Recognition With Weighted Complex Networks

In this paper we introduce a weighted complex networks model to investigate and recognize structures of patterns. The regular treating in pattern recognition models is to describe each pattern as a high-dimensional vector which however is insufficient to express the structural information. Thus, a number of methods are developed to extract the structural information, such as different feature extraction algorithms used in pre-processing steps, or the local receptive fields in convolutional networks. In our model, each pattern is attributed to a weighted complex network, whose topology represents the structure of that pattern. Based upon the training samples, we get several prototypal complex networks which could stand for the general structural characteristics of patterns in different categories. We use these prototypal networks to recognize the unknown patterns. It is an attempt to use complex networks in pattern recognition, and our result shows the potential for real-world pattern recognition. A spatial parameter is introduced to get the optimal recognition accuracy, and it remains constant insensitive to the amount of training samples. We have discussed the interesting properties of the prototypal networks. An approximate linear relation is found between the strength and color of vertexes, in which we could compare the structural difference between each category. We have visualized these prototypal networks to show that their topology indeed represents the common characteristics of patterns. We have also shown that the asymmetric strength distribution in these prototypal networks brings high robustness for recognition. Our study may cast a light on understanding the mechanism of the biologic neuronal systems in object recognition as well.

Complex networks constructed from irrational number sequences

In this paper, we construct (d, r) networks from sequences of different irrational numbers. In detail, segment an irrational number sequence of length M into groups of d digits which represent the nodes while two consecutive groups overlap by r digits (r = 0,1,...,d-1), and the undirected edges indicate the adjacency between two consecutive groups. (3, r) and (4, r) networks are respectively constructed from 14 different irrational numbers and their topological properties are examined. By observation, we find that network topologies change with different values of d, r and even sequence length M instead of the types of irrational numbers, although they share some similar features with traditional random graphs. We make a further investigation to explain these interesting phenomena and propose the identical-degree random graph model. The results presented in this paper provide some insight into distributions of irrational number digits that may help better understanding of the nature of irrational numbers.

Geographical constraints to range-based attacks on links in complex networks

In this paper, we studied range-based attacks on links in geographically constrained scale-free networks and found that there is a continuous switching of roles of short-and long-range attacks on links when tuning the geographical constraint strength. Our results demonstrate that the geography has a significant impact on the network efficiency and security; thus one can adjust the geographical structure to optimize the robustness and the efficiency of the networks. We introduce a measurement of the impact of links on the efficiency of the network, and an effective attacking strategy is suggested

Enhancing robustness and immunization in geographical networks

We find that different geographical structures of networks lead to varied percolation thresholds, although these networks may have similar abstract topological structures. Thus, strategies for enhancing robustness and immunization of a geographical network are proposed. Using the generating function formalism, we obtain an explicit form of the percolation threshold q(c) for networks containing arbitrary order cycles. For three-cycles, the dependence of q(c) on the clustering coefficients is ascertained. The analysis substantiates the validity of the strategies with analytical evidence.

Efficiency Dynamics on Two Coupled Small-World Networks

We investigate the effect of clusters in complex networks on efficiency dynamics by studying a simple efficiency model in two coupled small-world networks. It is shown that the critical network randomness corresponding to transition from a stagnant phase to a growing one decreases to zero as the connection strength of clusters increases. It is also shown for fixed randomness that the state of clusters transits from a stagnant phase to a growing one as the connection strength of clusters increases. This work can be useful for understanding the critical transition appearing in many dynamic processes on the cluster networks.

EFFICIENCY DYNAMICS ON SCALE-FREE NETWORKS WITH COMMUNITIES

The simple efficiency model is developed on scale-free networks with communities to study the effect of the communities in complex networks on efficiency dynamics. For some parameters, we found that the state of system will transit from a stagnant phase to a growing phase as the strength of community decreases.

The effect of human rhythm on packet delivery

In communication networks such as the Internet, the relationship between packet generation rate and time is similar to a rectangle wavefunction due to the rhythm of humans. Thus, we investigate the traffic dynamics on a network with a rectangle wavepacket generation rate. It is found that the critical delivering capacity parameter beta(c) (which separates the congested phase and the free phase) decreases significantly with the duty cycle r of the rectangle wave for package generation. And, in the congested phase, more collective generation of packets (smaller r) is helpful for decreasing the packet aggregation rate. Moreover, it is found that the congested phase can be divided into two regions, i.e., region1 and region2, where the distributions of queue lengths are nonlinear and linear, respectively. Also, the linear expression for the distribution of queue lengths in region2 is obtained analytically. Our work reveals an obvious effect of the rectangle wave on the traffic dynamics and the queue length distribution in the system, which is of essential interest and may provide insights into the designing of work-rest schedules and routing strategies.

Research of Face Detection System Applied for Detecting Faces with Complex Background and Illumination

An effective face detection system used for detecting multi pose frontal face in gray images is presented. Image preprocessing approaches are applied to reduce the influence of the complex illumination. Eye-analog pairing and improved multiple related template matching are used to glancing and accurate face detecting, respectively. To shorten the time cost of detecting process, we employ prejudge rules in checking candidate image segments before template matching. Test by our own face database with complicated illumination and background, the system has high calculation speed and illumination independency, and obtains good experimental results.

A more complex neuron in biomimetic pattern recognition

Biomimetic pattern recognition has been proposed for several years, but the discussion of its neuron was not very wide and deep. In this paper, we propose a new more complex neuron named M-neuron and give the application in the last part of the paper.

Kinetic Model Study on Enzymatic Hydrolysis of Cellulose Using Artificial Neural Networks

Enzymatic hydrolysis of cellulose was highly complex because of the unclear enzymatic mechanism and many factors that affect the heterogeneous system. Therefore, it is difficult to build a theoretical model to study cellulose hydrolysis by cellulase. Artificial neural network (ANN) was used to simulate and predict this enzymatic reaction and compared with the response surface model (RSM). The independent variables were cellulase amount X-1, substrate concentration X-2, and reaction time X-3, and the response variables were reducing sugar concentration Y-1 and transformation rate of the raw material Y-2. The experimental results showed that ANN was much more suitable for studying the kinetics of the enzymatic hydrolysis than RSM. During the simulation process, relative errors produced by the ANN model were apparently smaller than that by RSM except one and the central experimental points. During the prediction process, values produced by the ANN model were much closer to the experimental values than that produced by RSM. These showed that ANN is a persuasive tool that can be used for studying the kinetics of cellulose hydrolysis catalyzed by cellulase.

Structure characterization and physical properties of a complex with supramolecular architectures Co-2(2,6-DPC2Co(H2O)5 center dot 2H(2)O (DPC=2,6-pyridinedicarboxylate)

Reaction of 2,6-pyridinedicarboxylic with CoCl2 . 6H(2)O in aqueous solution give rise to a three-dimensional Complex CO2(2,6-DPC)(2)Co(H2O)(5).2H(2)O (DPC = 2,6-pyridinedicarboxylate) 1. It has been characterized by elemental analyses, infrared spectra (IR) spectrum, thermogravimetric (TG) analysis, EPR spectrum, and single crystal X-ray diffraction. The complex crystallizes in the P2(1)/c space group with a = 8.3906(3) Angstrom, b = 27.4005(8) Angstrom, c = 9.6192(4) A, alpha = 90.00degrees, beta = 98.327(2)degrees, gamma = 90.00degrees, V = 2188.20(14) Angstrom(3), Z = 4. There are two types of cobalt environments: Co(1) is coordinated by four oxygen atoms from four carboxyl groups and two nitrogen 2 atoms which are all from pdc(2). Co(2) is coordinated by six oxygen atoms, five from coordinated water molecules and one from a carboxyl of pdc(2) - of which the other oxygen atom is linked to the Co(1). The extensive intermolecular hydrogen bonds are formed in the crystal by means of the five coordinated water molecules.

Two new Cu-II coordination polymers: Studies of topological networks and water clusters

Two new Cull coordination polymers, namely [Cu-2(BDC)(2)(L)(4)(H2O)(2)]center dot 14H(2)O (1) and [Cu-1.5(BTC)(L)(1.5)(H2O)(0.5)]center dot 2H(2)O (2), where L = 1,1'-(1,4-butanediyl)bis(imidazole), BDC = 1,4-benzene dicarboxylate, and BTC = 1,3,5-benzenetricarboxylate, have been synthesized at room temperature. Complex 1 exhibits an unusual, square-planar, four-connected 2D (2)(6)4 net, which has been predicated by Wells. Interestingly, three types of water clusters, namely (H2O)(6), (H2O)(8), and (H2O)(10), are observed in the hydrogen-bonded layers constructed by the BDC ligands and water molecules. The BTC anion in compound 2 is coordinated to the Cu" cation as tetradentate ligand to form a (6(6))(2)(4(2)6(4)8(4))(2)(6(4)810) net containing three kinds of nonequivalent points, Thermogravimetric analyses (TGA) and IR spectra for 1 and 2 are also discussed in detail.

Room-temperature strategy for networked nonspherical gold nanostructures from Au(III)-[G-2]-CO2H dendrimer complex

The present work describes a convenient approach to fabricate networked nonspherical gold nanostructures by using [G-2]-CO2H dendrimer and toluene as capping and bridging agents in a CH2Cl2 and H2O biphasic system. A controlled linear assembly is achieved without the use of any catalyst at room temperature. UV-vis spectrum, transmission electron microscopy (TEM), selected area electron diffraction (SAED), and X-ray diffraction (XRD) analysis show that the product is well networked nanostructures with diameter of 4-10 nm and consists of coalesced face-centered cubic gold nanocrystals. Extended experiments reveal that both benzene and dimethylbenzene can also inhabit the gold ions to make them crosslinked, prolong the nucleation points and eventually facilitate the formation of the networks.

New high-dimensional networks based on polyoxometalate and crown ether building blocks

Three novel supramolecular assemblies constructed from polyoxometalate and crown ether building blocks, [(DB18C6)Na(H2O)(1.5)](2)Mo6O19.CH3CN, 1, and [{Na(DB18C6)(H2O)(2)}(3)(H2O)(2)]XMo12O40.6DMF.CH3CN (X = P, 2, and As, 3; DB18C6 = dibenzo-18-crown-6; DMF = N,N-dimethylfomamide), have been synthesized and characterized by elemental analyses, IR, UV-vis, EPR, TG, and single crystal X-ray diffraction. Compound 1 crystallizes in the tetragonal space group P4/mbm with a = 16.9701(6) Angstrom, c = 14.2676(4) Angstrom, and Z = 2. Compound 2 crystallizes in the hexagonal space group P6(3)/m with a = 15,7435(17) Angstrom, c = 30.042(7) Angstrom, gamma = 120degrees, and Z = 2. Compound 3 crystallizes in the hexagonal space group P6(3)/m with a = 15.6882(5) Angstrom, c = 29.9778(18) Angstrom, gamma = 120degrees, and Z = 2. Compound 1 exhibits an unusual three-dimensional network with one-dimensional sandglasslike channels based on the extensive weak forces between the oxygen atoms on the [Mo6O19](2-) polyoxoanions and the CH2 groups of crown ether molecules, Compounds 2 and 3 are isostructural, and both contain a novel semiopen cagelike trimeric cation [{Na(DB18C6)(H2O)(2)}(3)(H2O)(2)](3+). In their packing arrangement, an interesting 2-D "honeycomblike" "host" network is formed, in which the [XMo12O40](3-) (X = As and P) polyoxoanion "guests" resided.

From dissymmetrical mononuclear entities to centrosymmetrical heterotrinuclear complex with 2D supramolecular structure: synthesis, characterization, crystal structure, and magnetic properties

A new centrosymmetrical heterotrinuclear complex, {[Cu(oxbe)](2)Co(H2O)(2)}.2DMF.DMA with 2D supramolecular structure, has been obtained by the self-assembly of a dissymmetrical building block [Cu(oxbe)](-) with bivalent metal ion Co2+, where H(3)oxbe is dissymmetrical ligand N-benzoato-N'-(2-aminoethyl)oxamido, DMF = dimethylformamide, DMA = dimethylamine. Its structure was determined by single crystal X-ray analysis. The molecular structure is centrosymmetrical with the cobalt atom lying on an inversion center. Through the hydrogen bonds and d-pi stacking interactions, a 2D supramolecular structure is formed. This study exemplifies a new method for the assembly of supramolecular structure using a dissymmetrical brick. Magnetic susceptibility measurements (5-300 K) indicate that the central cobalt and terminal copper metal ions are antiferromagnetically coupled with J = -23.1 cm(-1).