一种基于块模糊增强的玉米田遥感图像边缘检测方法

针对高分一号卫星(GF-1)玉米田遥感图像中玉米田光谱复杂和地块边缘模糊导致的面积统计误差大的问题,本文提出一种块模糊增强和最小值边缘提取相结合的边缘检测方法进行玉米田地块分割处理,以减小面积统计误差。首先将彩色遥感图像从RGB变换到I¹I²I³彩色空间,提取出含丰富特征的单色图I¹;然后利用模糊理论对I¹进行基于块的增强处理;再对增强后的图像进行最小值边缘提取;最后利用Full Lambda-Schedule算法对区域边缘进行优化。通过与Canny和Sobel等边缘提取方法比较,证明本文的边缘检测结果能有效地分割出玉米田地块目标,减少了玉米田光谱复杂和边缘模糊带来的影响,检测出的边缘更符合玉米田实际分布,玉米田面积统计结果更符合实际。     

Generalized electron number distribution functions: real space versus orbital space descriptions

The algebraic expressions previously derived to compute the electron number distribution functions (EDF) for exhaustive partitions of the physical space into sharp-boundary atoms are generalized to allow for the use of fuzzy atoms and orbital-based partitions. In some of the latter, the atomic overlap matrix required to obtain the EDF is analytical. This makes them attractive alternatives to other definitions, as the one based on the atomic basins of the quantum theory of atoms in molecules (QTAIM), which are more physically sound but also much more demanding computationally. We will compute the EDF for a series of test molecules using different fuzzy and orbital-based partitions and compare them to QTAIM EDF. The effects of electron correlation and the use of the core approximation on the EDF will also be explored.     

Ecosystem discrimination and fingerprinting of Romanian propolis by hierarchical fuzzy clustering and image analysis of TLC patterns

The fingerprinting capacity of thin layer chromatography (TLC) and image analysis in the case of propolis samples collected in different area in Romania has been investigated. Fuzzy divisive hierarchical clustering approach was used as a powerful tool of samples discrimination and fingerprinting according to the geographical origin and local flora. The fuzzy partition and patterns obtained by membership degrees plot were in a very good agreement with floral origin and geographic location of Romanian propolis samples, and clearly illustrate the fuzziness concerning their similarities and difference. The results obtained strongly support that TLC via image analysis can be successfully employed in the fingerprinting methodologies if they are combined with appropriate fuzzy clustering method. The method developed in this paper might be also extended in the authenticity and origin control of fruits, herbs or derived products.     

Fuzzy theory. A promising tool for computerized chemistry

The basic notions of fuzzy theory are introduced along with the principles of fuzzy-set operations, fuzzy arithmetic and fuzzy logic. Applications in chemistry are outlined for dealing with incomplete and uncertain chromatographic or spectral data patterns, for comparing spectra or depth profiles as fuzzy functions, for applying fuzzy logic to reasoning in chemical data bases and for handling default knowledge.     

Modern Analysis

The important advances being made in modern analytical methods are indicative of the fundamental changes that are occuring in the theory and practice of “analytical chemistry”. “Information optimization” demands a new approach in teaching and research, and calls for the intergration of chemistry with other scientific and technical disciplines.     

Establishing a New Link between Fuzzy Logic,Neuroscience, and Quantum Mechanics through Bayesian Probability: Perspectives in Artificial Intelligence and Unconventional Computing

Human interaction with the world is dominated by uncertainty. Probability theory is a valuable tool to face such uncertainty. According to the Bayesian definition, probabilities are personal beliefs. Experimental evidence supports the notion that human behavior is highly consistent with Bayesian probabilistic inference in both the sensory and motor and cognitive domain. All the higher-level psychophysical functions of our brain are believed to take the activities of interconnected and distributed networks of neurons in the neocortex as their physiological substrate. Neurons in the neocortex are organized in cortical columns that behave as fuzzy sets. Fuzzy sets theory has embraced uncertainty modeling when membership functions have been reinterpreted as possibility distributions. The terms of Bayes’ formula are conceivable as fuzzy sets and Bayes’ inference becomes a fuzzy inference. According to the QBism, quantum probabilities are also Bayesian. They are logical constructs rather than physical realities. It derives that the Born rule is nothing but a kind of Quantum Law of Total Probability. Wavefunctions and measurement operators are viewed epistemically. Both of them are similar to fuzzy sets. The new link that is established between fuzzy logic, neuroscience, and quantum mechanics through Bayesian probability could spark new ideas for the development of artificial intelligence and unconventional computing.     

Nonlinear characteristics of the quantitative relationship between the glass‐transition temperature and the structure of homopolymers

Fuzzy set theory was used to study the relationship between the glass‐transition temperature (T_g) and structure of homopolymers. The method can map the relationship and give the T_g for 235 polymers with a standard deviation of 8 K (the confidence bound was 90%). The entropy of the fuzziness was used to quantitatively describe the interactions among groups. The method was used to predict the T_g of 10 polymers not included in the 235 polymers, with a standard deviation of 9 K (the confidence bound was 90%). The study demonstrates again that fuzzy set theory can be effectively used to investigate the quantitative structure–property relationship of polymers. © 2002 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 40: 2164–2169, 2002     

用模糊数学评价中成药质量的方法研究

本研究应用模糊数学中ISODATA(Interactive Self-Organizing Data Analysis Technique A)聚类分析法,把不同厂家的同一品种中成药分成五个等级,即Ⅰ、Ⅱ、Ⅲ、Ⅳ、Ⅴ级品。并根据此分级结果构造一个多元隶属函数,提出一种模糊模型的等级识别法,为制定各类中成药质量判别标准提供了依据。本文用十个厂家共三十个批号的冠心苏合丸验证,效果满意。     

Analytical evaluation of Fukui functions and real-space linear response function

Many useful concepts developed within density functional theory provide much insight for the understanding and prediction of chemical reactivity, one of the main aims in the field of conceptual density functional theory. While approximate evaluations of such concepts exist, the analytical and efficient evaluation is, however, challenging, because such concepts are usually expressed in terms of functional derivatives with respect to the electron density, or partial derivatives with respect to the number of electrons, complicating the connection to the computational variables of the Kohn-Sham one-electron orbitals. Only recently, the analytical expressions for the chemical potential, one of the key concepts, have been derived by Cohen, Mori-Sánchez, and Yang, based on the potential functional theory formalism. In the present work, we obtain the analytical expressions for the real-space linear response function using the coupled perturbed Kohn-Sham and generalized Kohn-Sham equations, and the Fukui functions using the previous analytical expressions for chemical potentials of Cohen, Mori-Sánchez, and Yang. The analytical expressions are exact within the given exchange-correlation functional. They are applicable to all commonly used approximate functionals, such as local density approximation (LDA), generalized gradient approximation (GGA), and hybrid functionals. The analytical expressions obtained here for Fukui function and linear response functions, along with that for the chemical potential by Cohen, Mori-Sánchez, and Yang, provide the rigorous and efficient evaluation of the key quantities in conceptual density functional theory within the computational framework of the Kohn-Sham and generalized Kohn-Sham approaches. Furthermore, the obtained analytical expressions for Fukui functions, in conjunction with the linearity condition of the ground state energy as a function of the fractional charges, also lead to new local conditions on the exact functionals, expressed in terms of the second-order functional derivatives. We implemented the expressions and demonstrate the efficacy with some atomic and molecular calculations, highlighting the importance of relaxation effects.     

Viscoelasticity of stretched polymer chains: Analytical theory and computer-aided simulation

The viscoelasticity of stretched polymer chains has been studied by the method of collisional dynamics. To this end, time correlation functions of the fluctuations of the microscopic stress tensor are modeled and relaxation moduli are expressed. Before, for stretched polymer networks, correlation functions used to be calculated in terms of an approximate theory that allowed one to estimate the strain dependences of loss modulus. The calculated dependences are shown to agree qualitatively with the results of measurements performed over a wide interval of strains, including prefracture strains. This theory is verified by comparing the time correlation functions of stress tensor fluctuations for a single stretched chain; these functions are found by computer-aided simulation and calculated on the basis of the existing analytical theory. In this case, a simple theory is adopted according to which a polymer molecule represents a chain composed of N atoms connected by freely jointed elastic bonds. The first and Nth atoms of this chain are attached by harmonic springs to immobile points located at a fixed distance. The decay of time correlation functions under study can be resolved into three stages. After a short initial interval provided by local motions, one can observe a region of power-law decay, which is followed by monoexponential decay at long times. The results of computer-aided simulation generally agree with the predictions of analytical theory. Certain discrepancies primarily concern the dependences of the exponent of power-law relaxation on the degree of chain stretching.     

Higher order alchemical derivatives from coupled perturbed self-consistent field theory

We present an analytical approach to treat higher order derivatives of Hartree-Fock (HF) and Kohn-Sham (KS) density functional theory energy in the Born-Oppenheimer approximation with respect to the nuclear charge distribution (so-called alchemical derivatives). Modified coupled perturbed self-consistent field theory is used to calculate molecular systems response to the applied perturbation. Working equations for the second and the third derivatives of HF/KS energy are derived. Similarly, analytical forms of the first and second derivatives of orbital energies are reported. The second derivative of Kohn-Sham energy and up to the third derivative of Hartree-Fock energy with respect to the nuclear charge distribution were calculated. Some issues of practical calculations, in particular the dependence of the basis set and Becke weighting functions on the perturbation, are considered. For selected series of isoelectronic molecules values of available alchemical derivatives were computed and Taylor series expansion was used to predict energies of the "surrounding" molecules. Predicted values of energies are in unexpectedly good agreement with the ones computed using HF/KS methods. Presented method allows one to predict orbital energies with the error less than 1% or even smaller for valence orbitals.     

恶臭成分的仪器分析方法研究进展

对恶臭污染物质的测定内容包括恶臭物质的总体浓度、具体成分及相应的浓度水平。随着痕量气体分析技术水平的提高,增加受控恶臭污染物的种类成为可能。恶臭物质因种类繁多、性质差异大,分析方法多种多样。该文根据不同恶臭物质的物理、化学特性,结合国内外最先进的分析技术和标准,从恶臭物质样品采集、前处理以及不同分析仪器的选择方面,综述了目前恶臭成分的仪器分析方法研究进展。     

Application of reference materials for quality assessment in neutron activation analysis-use of information theory

It is generally accepted that an analytical procedure can be regarded as an information production system yielding information on the composition of the analyzed sample. Thus, information theory can be useful and the quantities characterizing the information properties of an analytical method may be applied not only as evaluation criteria but also as objective functions in the optimization. The usability of information theory is demonstrated on the example of neutron activation analysis. Both precision and bias of NAA results are taken into account together with the possible use of reference materials for quality assessment. The influence of the above-mentioned parameters on information properties such as information gain and profitability of NAA results is discussed in detail. It has been proved that information theory is especially useful in choosing suitable reference materials for the quality assessment of routine analytical procedures not only with respect to matrix and analyte concentration in the sample but also to concentrations and uncertainties of certified values in the CRM used. In the extreme trace analysis, CRMs with relatively large uncertainties and very low certified concentrations can still yield rather high information gain of results.     

Pattern recognition based on fuzzy observations for spectroscopic quality control and chromatographic fingerprinting

The quality of multicomponent samples from one or several groups of samples can be monitored by a pattern recognition method. The method is based on profiles of sample quality, which are obtained by means of a multicomponent analytical technique (e.g., ultraviolet spectroscopy or chromatography), and data reduction is done with the aid of fuzzy set theory. The advantages of the method in cases of overlapping and non-additive signals are outlined for quality control of analgesic tablets by ultraviolet spectroscopy. Its performance in the case of highly uncertain data patterns is demonstrated for classification of protein samples by chromatography.     

分析化学的“昨天、今天和明天”

简述了分析化学的发展历史。分析化学的"昨天",从基于物理化学的溶液理论,以目视可见为工具的"化学分析",进入以物理方法为基础的仪器分析,因此有人提出"化学正在走出分析化学";分析化学的"今天",因为它的主体任务是解决物质的分子原子结构和成分,所以又回归化学领域;对分析化学的"明天"寄厚望,分析化学走出历来仅仅以"为他人报告提供数据"的技术支持者的角色,成为"实际问题解决者",利用分析化学中综合分析的"剖析技术",为新产品开发创制的"反工艺研究"做出独特的贡献。     

Communication: extended multi-state complete active space second-order perturbation theory: energy and nuclear gradients

The extended multireference quasi-degenerate perturbation theory, proposed by Granovsky [J. Chem. Phys. 134, 214113 (2011)], is combined with internally contracted multi-state complete active space second-order perturbation theory (XMS-CASPT2). The first-order wavefunction is expanded in terms of the union of internally contracted basis functions generated from all the reference functions, which guarantees invariance of the theory with respect to unitary rotations of the reference functions. The method yields improved potentials in the vicinity of avoided crossings and conical intersections. The theory for computing nuclear energy gradients for MS-CASPT2 and XMS-CASPT2 is also presented and the first implementation of these gradient methods is reported. A number of illustrative applications of the new methods are presented.     

A new approach to the determination of good action-angle variables for coupled oscillator systems

A theory of action-angle variables for coupled oscillator systems is developed which involves solving the Schrödinger equation using a basis of WKB eigenfunctions, then using the logarithm of the resulting wavefunction to define the generator for the canonical transformation which determines the action-angle variables. This theory is based on the marriage between Miller's method for solving the Hamilton-Jacobi equation using the logarithm of the generating function, and the Ratner-Buch-Gerber method for solving the Schrödinger equation using WKB basis functions. A perturbation-theory analysis of this theory indicates that the semiclassical eigenvalues and canonical transformations obtained from it should become identical to their exact classical counterparts in the limit of large actions for each vibrational mode. Two methods for systematically improving the theory for the lower eigenstates are also proposed. Numerical applications of the theory are presented for two systems, the Morse oscillator and the Henon-Heiles two-mode hamiltonian. The resulting semiclassical eigenvalues are in excellent agreement with their exact quantum counterparts, with the magnitude of the error roughly independent of the energy of the eigenstate. Analogous good agreement is found in comparing the approximate and exact classical canonical transformations. In particular, for the Morse oscillator, good results are obtained for certain higher energy states where second-order classical perturbation theory makes serious errors. Other information examined includes surfaces of section for the Henon-Heiles system (comparing the analytical functions obtained from the present theory with results based on exact trajectory calculations) and vibrational distributions chosen to simulate trajectory calculations (using the present theory to determine bin boundaries for a histogram calculation). Again, the comparison in each case with accurate results is excellent, with maximum errors in action calculations of 0.02 h, and in angle calculations of 0.01 rad.     

Miniaturization in sample treatment for environmental analysis

The increasing demand for faster, more cost-effective and environmentally friendly analytical methods is a major incentive to improve the classical procedures used for sample treatment in environmental analysis. In most classical procedures, the use of rapid and powerful instrumental techniques for the final separation and detection of the analytes contrasts with the time-consuming and usually manual methods used for sample preparation, which slows down the total analytical process. The efforts made in this field in the past ten years have led to the adaptation of existing methods and the development of new techniques to save time and chemicals, and improve overall performance. One route has been to develop at-line or on-line and, frequently, automated systems. In these approaches, miniaturization has been a key factor in designing integrated analytical systems to provide higher sample throughput and/or unattended operation. Selected examples of novel developments in the field of miniaturized sample preparation for environmental analysis are used to evaluate the merits of the various techniques on the basis of published data on real-life analyses of trace-level organic pollutants. Perspectives and trends are briefly discussed.     

Quantitative fuzzy neural network for analytical determination

A quantitative fuzzy neural network (Q-FNN) for pattern recognition in analytical determination is reported in this paper. The fuzzy neural network (FNN) combines a fuzzy logic system with an artificial neural network (ANN) so that it has both advantages of a high training speed and strong anti-interference. Importantly, the analytical concept of relative error (RE) in quantitative determination has been integrated into FNN so that the Q-FNN provides a very good quantitative capability in chemical analysis, and prevents the system from an over-fitting problem. The logarithm curve with noise in terms of analytical response versus concentration is calibrated by trained FNN and a close approximation to the ideal one without noise is obtained. The Q-FNN has been applied to the concentration determination of freon in the presence of interference gases. The prediction error for a test set in quantification is less than 10% while no qualitative mistake is observed, implying that the quantitative FNN has sustained the feature of pattern recognition. The results indicate that the Q-FNN has obvious advantages not only in converging speed, but also in the quantitative accuracy over the ANN.