Artificial neural network applied to diagnosis of lung cancer

Artificial neural network(ANN) approach was applied to classification of normal persons and lung cancer patients based on the metal content of hair and serum samples obtained by inductively coupled plasma atomic emission spectrometry (ICP-AES) for the two groups. This method was verified with independent prediction samples and can be used as an aiding means of the diagnosis of lung cancer. The case of predictive classification with one element missing in the prediction samples was studied in details, The significance of elements in hair and serum samples for classification prediction was also investigated.

Compensation effect of polyimide thin films on normally white twisted nematic liquid crystal displays

The disadvantages of Normally White Twisted Nematic Liquid Crystal Display (NW-TN-LCD) were discussed. The reason that the negative birefringent polyimide thin films were used to compensate NW-TN-LCD to decrease off-axis leakage, improve contrast ratios and enlarge viewing angles was explained in this paper. A certain polyimide thin film was taken as an example to show compensation effect on NW-TN-LCD.

Quantitative structure-property relationships for colour reagents and their colour reactions with cerium using computational neural networks

Quantitative structure-activity/property relationships (QSAR/QSPR) studies have been exploited extensively in the designs of drugs and pesticides, but few such studies have been applied to the design of colour reagents. In this work, the topological indices A(x1)-A(x3) suggested in this laboratory were applied to multivariate analysis in structure-property studies. The topological indices of 43 phosphone bisazo derivatives of chromotropic acid were calculated. The structure-property relationships between colour reagents and their colour reactions with cerium were studied using A(x1-Ax3) indices with satisfactory results. The purpose of this work was to establish whether QSAR can be used to predict the contrasts of colour reactions and in the longer term to be a helpful tool in colour reagent design.

Prediction of molar absorptivities of color reagents during their color reactions with cerium using multiple regression analysis and neural network

A quantitative structure-property study has been made on the relationship between molar absorptivities (epsilon) of asymmetrical phosphone bisazo derivatives of chromotropic acid and their color reactions with cerium by multiple regression analysis and neural network. The new topological indices A(x1) - A(x3) suggested in our laboratory and molecular connectivity indices of 43 compounds have been calculated. The results obtained from the two methods are compared. The neural network model is superior to the regression analysis technique and gave a prediction which was sufficiently accurate to estimate the molar absorptivities of color reagents during their color reactions with cerium.

Study on Phenol Compounds Using Multiple Regression and Neural Network Methods

In this paper, the molecular connectivity indices and the electronic charge parameters of forty-eight phenol compounds nave been calculated. and applied for studying the relationship between partition coefficients and structure of phenol compounds. The results demonstrate that the properties of compounds can be described better with selective parameters, and the results obtained by neural network are superior to that by multiplle regression.

Quantitative structure-property relationships for colour reagents and their colour reactions with ytterbium using regression analysis and computational neural networks

In this paper, the new topological indices A(x1)-A(x3) suggested in our laboratory and molecular connectivity indices have been applied to multivariate analysis in structure-property studies. The topological indices of twenty asymmetrical phosphono bisazo derivatives of chromotropic acid have been calculated. The structure-property relationships between colour reagents and their colour reactions with ytterbium have been studied by A(x1)-A(x3) indices and molecular connectivity indices with satisfactory results. Multiple regression analysis and neural networks were employed simultaneously in this study.

QUANTITATIVE STRUCTURE-ACTIVITY-RELATIONSHIPS FOR TOXICITY OF PHENOLS USING REGRESSION-ANALYSIS AND COMPUTATIONAL NEURAL NETWORKS

Quantitative structure-toxicity models were developed that directly link the molecular structures of a et of 50 alkYlated and/or halogenated phenols with their polar narcosis toxicity, expressed as the negative logarithm of the IGC50 (50% growth inhibitor

CHARGE COMPENSATION AND LUMINOUS CENTERS IN CAF2-CE3+

We synthesize some powder phosphors of CaF2:Ce3+ under different reaction conditions, find three luminous centres, and demonstrate that each luminous centre is formed with different charge compensation procedures.

CHARGE COMPENSATION AND VALENCY STABILITY OF EU(II)-DOPED KMGF3 CRYSTAL

The spectrochemistry of Eu2+-doped perovskite KMgF3 was examined and discussed. Eu2+ can replace some of the K+ in the KMgF3 crystal, and simultaneously the corresponding cation hole can be compensated with the F- or O2- in the matrix. The emission intensity of Eu2+ due to the f --> f transition increased when Na+, Rb+ or F- was doped in KMgF3:Eu2+. Two mechanisms of charge compensation were proposed. No obvious valence change of Eu2+ occurred in KMgF3:Eu2+ after calcinating at high temperature, e.g. 900-degrees-C. It was found that the valence stability of Eu2+ improved after incorporation into the matrix.

Phenoloxidase, a marker enzyme for differentiation of the neural ectoderm and the epidermal ectoderm during embryonic development of amphioxus Branchiostoma belcheri tsingtaunese

The development of phenoloxidase during amphioxus embryogenesis was spectrophotometrically and histochemically studied for the first time in the present study. It was found that (1) PO activity initially appeared in the general ectoderm including the neural ectoderm and the epidermal ectoderm at the early neurala stage but not in the mesoderm or the endoderm, and (2) PO activity disappeared in the neural plate cells but remained unchanged in the epidermal cells when the neural plate was morphologically quite distinct from the rest of the ectoderm. It is apparent that PO could serve as a marker enzyme for differentiation of the neural ectoderm from the epidermal ectoderm during embryonic development of amphioxus. (C) 2000 Elsevier Science ireland Ltd. All rights reserved.

Neural network retrieval of ocean surface parameters from SSM/I data

A new algorithm based on the multiparameter neural network is proposed to retrieve wind speed (WS), sea surface temperature (SST), sea surface air temperature, and relative humidity ( RH) simultaneously over the global oceans from Special Sensor Microwave Imager (SSM/I) observations. The retrieved geophysical parameters are used to estimate the surface latent heat flux and sensible heat flux using a bulk method over the global oceans. The neural network is trained and validated with the matchups of SSM/I overpasses and National Data Buoy Center buoys under both clear and cloudy weather conditions. In addition, the data acquired by the 85.5-GHz channels of SSM/I are used as the input variables of the neural network to improve its performance. The root-mean-square (rms) errors between the estimated WS, SST, sea surface air temperature, and RH from SSM/I observations and the buoy measurements are 1.48 m s(-1), 1.54 degrees C, 1.47 degrees C, and 7.85, respectively. The rms errors between the estimated latent and sensible heat fluxes from SSM/I observations and the Xisha Island ( in the South China Sea) measurements are 3.21 and 30.54 W m(-2), whereas those between the SSM/ I estimates and the buoy data are 4.9 and 37.85 W m(-2), respectively. Both of these errors ( those for WS, SST, and sea surface air temperature, in particular) are smaller than those by previous retrieval algorithms of SSM/ I observations over the global oceans. Unlike previous methods, the present algorithm is capable of producing near-real-time estimates of surface latent and sensible heat fluxes for the global oceans from SSM/I data.

基于神经网络的水泥生料配料多目标优化设计方法

为了降低生料成分的不确定性给水泥生料质量控制系统带来的影响,提出了率值补偿的控制策略.分别为三率值创建目标函数,并利用状态空间搜索策略解决多目标优化问题.针对初始样本空间不能覆盖所有样本的问题,提出了基于神经网络的估算模型,对初始样本空间进行拓扑.通过估价函数对状态空间中的状态量进行评价,得到最优的率值状态量;根据率值对原料配比进行调整,最后使率值偏差得到补偿,同时使给配比造成的波动最小.工业实验结果表明,生料的质量合格率由原来的30%提高到50%,该系统能有效地对配料过程进行优化控制.证明了基于神经网络的状态空间搜索策略为水泥生料配料多目标寻优问题提供了一种可行的方法。