WAVELET TRANSFORM IN FRACTAL IMAGE ENCODING

This paper presents some results of the relation between wavelet transform and fractal transform. The wavelet transform of the attractor of fractal transform posseses translational and scale invariance. So we speed the fractal image encoding by testing the invariance of the wavelet transform appropriate for image encoding. The classfication scheme of range blocks by wavelet transform is given in this paper.     

Optimization technique based on learning automata

Optimization techniques are finding increasingly numerous applications in process design, in parallel to the increase of computer sophistication. The process synthesis problem can be stated as a largescale constrained optimization problem involving numerous local optima and presenting a nonlinear and nonconvex character. To solve this kind of problem, the classical optimization methods can lead to analytical and numerical difficulties. This paper describes the feasibility of an optimization technique based on learning systems which can take into consideration all the prior information concerning the process to be optimized and improve their behavior with time. This information generally occurs in a very complex analytical, empirical, or know-how form. Computer simulations related to chemical engineering problems (benzene chlorination, distillation sequence) and numerical examples are presented. The results illustrate both the performance and the implementation simplicity of this method.Nomenclature c _i penalty probability - cp precision parameter on constraints - D variation domain of the variablex - f(·) objective function - g(·) constraints - i,j indexes - k iteration number - N number of actions - P probability distribution vector - p _i ith component of the vectorP as iterationk - r number of reactors in the flowsheet - u(k) discrete value or action chosen by the algorithm at iterationk - u _i discrete value of the optimization variable in [u _min,u _max] - u _min lowest value of the optimization variable - u _max largest value of the optimization variable - Z random number - x variable for the criterion function - xp precision parameter on criterion function - W(k) performance index unit output at iterationk - ₀, ₁ reinforcement scheme parameters - _p sum of the probability distribution vector components     

Schedule-an expert-like system for machine scheduling

The construction of an expert-like system for machine scheduling called SCHEDULE is presented. Essential parts of SCHEDULE were developed by students in a laboratory course Operations Research on Microcomputers at the University of Karlsruhe, Germany. SCHEDULE consists of the components data base, knowledge base, inference engine, explanation facility, dialog component, and knowledge acquisition component. The knowledge base contains an algorithm base for solving different types of scheduling problems. To establish the rules of the knowledge base the well-known three-field classification of deterministic machine scheduling problems and the concept of the reduction digraph are exploited. Experiences gained during building and demonstrating SCHEDULE are reported.     

过渡金属络合物成键本质分析的常用方法

过渡金属络合物中过渡金属与配体间所形成的化学键的成键本质,可以在理论化学基础上,采用定量的方法进行分析。本文重点以铁羰基络合物为例,对常用的分析方法,如自然键轨道方法(NBO)、电荷分解分析(CDA)、分子中的原子(AIM)拓扑分析方法以及ETS和EDA能量分解方法等,在应用中的优缺点进行了分析和评述。借助于这些方法提供的电荷、能量和电子密度等配分项可以深刻认识和理解过渡金属-配体间形成的化学键的成键本质。     

Simulation of13C NMR chemical shifts for polychlorinated and polybrominated oxybenzenes with two-particle increment scheme

A two-particle system of OY-Cl and OY-Br mixed increments for predicting¹³C NMR chemical shifts of polyhalogenated polyoxybenzenes has been developed. It has been found that only theortho- and para-interactions of the OY and Hal substituents contribute significantly to the¹³C chemical shifts and that theortho-effects of the OY located between Ha1 and H and those of the OY located between two Ha1 atoms are different. Additional effects are due to solvating solvents. The increment scheme is predictive over the whole class of compounds under consideration and may be realized on personal computers.Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 4, pp. 617–624, April, 1994.     

Properties of a genetic algorithm extended by a random self-learning operator and asymmetric mutations: A convergence study for a task of powder-pattern indexing

Genetic algorithms represent a powerful global-optimisation tool applicable in solving tasks of high complexity in science, technology, medicine, communication, etc. The usual genetic-algorithm calculation scheme is extended here by introduction of a quadratic self-learning operator, which performs a partial local search for randomly selected representatives of the population. This operator is aimed as a minor deterministic contribution to the (stochastic) genetic search. The population representing the trial solutions is split into two equal subpopulations allowed to exhibit different mutation rates (so called asymmetric mutation). The convergence is studied in detail exploiting a crystallographic-test example of indexing of powder diffraction data of orthorhombic lithium copper oxide, varying such parameters as mutation rates and the learning rate. It is shown through the averaged (over the subpopulation) fitness behaviour, how the genetic diversity in the population depends on the mutation rate of the given subpopulation. Conditions and algorithm parameter values favourable for convergence in the framework of proposed approach are discussed using the results for the mentioned example. Further data are studied with a somewhat modified algorithm using periodically varying mutation rates and a problem-specific operator. The chance of finding the global optimum and the convergence speed are observed to be strongly influenced by the effective mutation level and on the self-learning level. The optimal values of these two parameters are about 6 and 5%, respectively. The periodic changes of mutation rate are found to improve the explorative abilities of the algorithm. The results of the study confirm that the applied methodology leads to improvement of the classical genetic algorithm and, therefore, it is expected to be helpful in constructing of algorithms permitting to solve similar tasks of higher complexity.     

基于超星学习通平台的有机化学录播课教学实践

由于新型冠状病毒肺炎疫情,高校延期开学。为了实现"停课不停教、停课不停学",需要积极开展在线教学。本文基于超星学习通平台,开展了有机化学课程录播课教学实践,为高校教师网络教学提供一定的参考。     

Hydration scheme of uracil and cytosine

The comparison of a pure electrostatic approximation and complete supermolecule SCF ab initio computations on the hydration scheme of uracil and cytosine shows that the electrostatic procedure is capable to reproduce the general aspects of the results of the supermolecule treatment provided that different distances of shortest approach be adopted for the distances between the oxygen of water and the nitrogen of NH₂ or NH groups or the oxygen of C-O groups on the one hand and the oxygen of water and pyridine-type nitrogens on the other hand.     

THPep: A machine learning-based approach for predicting tumor homing peptides

In the present era, a major drawback of current anti-cancer drugs is the lack of satisfactory specificity towards tumor cells. Despite the presence of several therapies against cancer, tumor homing peptides are gaining importance as therapeutic agents. In this regard, the huge number of therapeutic peptides generated in recent years, demands the need to develop an effective and interpretable computational model for rapidly, effectively and automatically predicting tumor homing peptides. Therefore, a sequence-based approach referred herein as THPep has been developed to predict and analyze tumor homing peptides by using an interpretable random forest classifier in concomitant with amino acid composition, dipeptide composition and pseudo amino acid composition. An overall accuracy and Matthews correlation coefficient of 90.13% and 0.76, respectively, were achieved from the independent test set on an objective benchmark dataset. Upon comparison, it was found that THPep was superior to the existing method and holds high potential as a useful tool for predicting tumor homing peptides. For the convenience of experimental scientists, a web server for this proposed method is provided publicly at http://codes.bio/thpep/.     

Modelisation of the Electric Field Linear Response of an Infinite Aggregate of All-Trans Hexatriene Chains by Electrostatic Interaction Model

A classical electrostatic polarization scheme using the additive distribution procedure has been applied to determine the longitudinal polarizability of an all-trans hexatriene molecule in an infinite stretched fiber. The parameters have been derived from ab initio CPHF/6-31G calculations and the electrostatic scheme has been validated via comparison with ab initio results on small clusters. Upon packing the polarizability of all-trans hexatriene increases by 7%. This small increase results from the balance between the enhancement of the polarizability due to collinear packing and the reduction associated with lateral packing.