Wavelet Numerical Solutions for Weakly Singular Fredholm Integral Equations of the Second Kind

Daubechies interval wavelet is used to solve numerically weakly singular Fredholm integral equations of the second kind. Utilizing the orthogonality of the wavelet basis,the integral equation is reduced into a linear system of equations. The vanishing moments of the wavelet make the wavelet coefficient matrices sparse,while the continuity of the derivative functions of basis overcomes naturally the singular problem of the integral solution. The uniform convergence of the approximate solution by the wavelet method is proved and the error bound is given. Finally,numerical example is presented to show the application of the wavelet method.     

Research on the Bit Computation Model for Time Variable Channel Bandwidth

For the encoding bit-rate problem in H.264 wireless video communication,this paper analyzes the bit-rate computation model and the Mean Square Error distortion model,establishes the relation between the quantization parameter of the encoding bit-rate and the intra frame refresh rate of the macro block,and put forward a new ideal about the coding rate on the basis of general binomial computation model theory. Furthermore,this method not only can adaptively adjust the bit allocation and quantization parameter and prevents buffer from overflowing downward or upward under given network bandwidth,but also can apply the rate-distortion to optimize the solution method,control the encoding bits accurately and optimizes the allocation between the intra and inter frame encoding macro block.     

Blurred Defocused Image Restoration Based on FRFT

A technique for restoring the blurred image resulted from defocusing of the lens is proposed in this paper, which is based on fractional Fourier transform （FRFT）.The FRFT, as a powerful tool for the analysis of time-varying signals, is closely connected with the optical imaging system. FRFT also can describe optical imaging process just like Fresnel diffractions, so a defocused imaging model based on FRFT is established to explain the blur phenomena of defocusing image. The defocused imaging model is greatly different from the traditional point spread function （PSF） model, and enables to uncover the blur nature of non-focus image. Then, an image restoration method using the novel model is proposed to handle the blurred defocused image. The method adopted a new iterative phase retrieval approach which can approximately estimate phase signals from intensity signals of a single defocused image by means of FRFT. Restoring image may acquire sharp image by implementing inverse FRFT on complex image signal made from the estimated phase signals and intensity signals. Experimental results demonstrate that the method is effective in restoring blurred defocused image.     

Stability Analysis of Stochastic Swarm Systems

In this paper,we present a model of stochastic swarm system and prove the stability of this kind of systems. We establish the stable aggregating behavior for the group using a coordination control scheme. This individual-based control scheme is a combination of attractive and repulsive interactions among the individuals in the group,which ensures the cohesion of the group and collision avoidance among the individuals. The dynamics of each individual depends on the relative positions between the individuals and the influences of the random disturbances. Under the influences of the noises,this position-based control strategy still generates the stable aggregating behavior harmoniously for the group and the self-organized swarm pattern is formed.     

Synthesis, Characterization and Calorimetry of Ni（C4H8N2O3）2Cl2

A coordination complex was synthesized from NiCl2 and dipeptide glycylglycine（GG）. It was characterized by element analysis, NMR and TG methods, and then was determined to be Ni（C4HsN2O3）2Cl2. Using an isoperibolic reaction calorimeter, the standard molar enthalpy of formation of Ni（GG）2Cl2（solid） has been determined to be -（1 674.66±2.02） kJ · mol^-1 at 298.15 K.     

Research of Inclusion Complexation of 4,4＇-Thiodiphenol Effected by β-Cyclodextrin in Aqueous Solutions and the Effect on Photodegradation

The inclusion behavior of 4, 4＇ -Thiodiphenol （TDP）, a typical bisphenol and endocrine disruptor, reacts with β-cyclodextrin （β-CD） in aqueous solutions has been investigated by means of UV absorption spectrum and quantum-chemical calculation with Gaussian 98 software. The results show that the inclusion behavior of TDP is quite different in acidic solutions （pH 5.9） from that in alkaline solutions （pH 10.0）. This behavior difference is attributed to the different formula structures in aqueous solutions at acidic and alkaline pH values that are demonstrated by quantum- chemical modeling and calculation. TDP forms a 1 ： 1 fl-CD inclusion complex in aqueous solutions. The equiiibrium constant K was calculated to be 553.49 L/mol at pH 5.9 and 1 318.20 L/mol at pH 10.0 respectively for the inclusion complex reaction by using the modified Benesi-Heldbrand equation. After inclusion TDP＇s structure is changed especially at the inclusion part with the bond order becoming larger, which results in inhibitive photodegradation during direct photooxidation and H2O2 assisted photooxidation.     

Optimizing Conditions of Enhancing Granule Sludge Concentration and Performance

An expanded granular sludge bed （EGSB） reactor was adopted to study the influence factors and rule of enhancing granular sludge concentration and performance. The experiment was performed at 33 ℃, pH 6.0-8.0 with continuous flow by adding proper quantity of nutritional trace elements. The results show that SLR was the key of steady operation of EGSB reactor. The increment of the granular sludge was influenced by volume loading rate （VLR）, liquid up-flow velocity and sludge loading rate （SLR）. Concentration of granular sludge increased rapidly when liquid up-flow velocity was over 0.94 m · h^-1 with SLR being at 1.0-2.0 d ^-1. With the propriety parameters： liquid up-flow velocity 2.52 m · h^-1, SLR 1.0-2.2 d^-1 and VLR 8.2-13.1 kg · m ^3 · d^-1, 23 days＇ continuous operation resulted in an increment by over 80% of granular sludge concentration in the EGSB reactor, plus good granular sludge property.     

Soil Organic Carbon Loss under Different Slope Gradients in Loess Hilly Region

Based on field runoff plots observation and sample analysis, the effect of slope gradient on soil organic carbon loss was studied under natural rainfall conditions in loess hilly region. The results showed that with slope gradient increasing （from10° to 30°）, the changing trend of soil erosion intensity （A） was A20°〉A30°〉A15°〉A10°〉A25°, suggesting that slope gradient between 20° and 25° was a critical degree ranger to exist. Soil organic carbon loss was mainly influenced by soil erosion intensity, appearing the same trend as did soil erosion intensity with increasing slope gradient. Soil erosion results in organic carbon enrichment in sediment. Average enrichment ratios of five runoff plots varied from 2.27 to 3.74, and decreased with increasing erosion intensity and slope gradient. The decrease of surface runoff and soil erosion is the key to reduce soil organic carbon loss.     

A New Generalized Similarity-Based Topic Distillation Algorithm

The procedure of hypertext induced topic search based on a semantic relation model is analyzed, and the reason for the topic drift of HITS algorithm was found to prove that Web pages are projected to a wrong latent semantic basis. A new concept-generalized similarity is introduced and, based on this, a new topic distillation algorithm GSTDA（generalized similarity based topic distillation algorithm） was presented to improve the quality of topic distillation. GSTDA was applied not only to avoid the topic drift, but also to explore relative topics to user query. The experimental results on 10 queries show that GSTDA reduces topic drift rate by 10% to 58% compared to that of HITS（hypertext induced topic search） algorithm, and discovers several relative topics to queries that have multiple meanings.     

Research on Bayesian Network Based User＇s Interest Model

It has very realistic significance for improving the quality of users＇ accessing information to filter and selectively retrieve the large number of information on the Internet. On the basis of analyzing the existing users＇ interest models and some basic questions of users＇ interest （representation, derivation and identification of users＇ interest）, a Bayesian network based users＇ interest model is given. In this model, the users＇ interest reduction algorithm based on Markov Blanket model is used to reduce the interest noise, and then users＇ interested and not interested documents are used to train the Bayesian network. Compared to the simple model, this model has the following advantages like small space requirements, simple reasoning method and high recognition rate. The experiment result shows this model can more appropriately reflect the user＇s interest, and has higher performance and good usability.