复方降脂中药的性味归经与药效的BPNN研究

针对复方中药药效与其性味归经之间复杂的、不确定的关系,建立适于复方降脂中药的BP神经网络模型,运用Matlab快速预测复方降脂中药的药效指标。经验证,该方法为一种快速、可靠的方法。     

性味归经与抗衰老药效的BP神经网络研究

针对中药药效与其性味归经之间复杂的、不确定的关系,运用人工神经网络的理论和方法,建立中药抗衰老药效的BP神经网络模型,通过实例对抗衰老指标进行评价分析。经验证,用BP神经网络方法评价中药抗衰老药效是一种快速、可靠的方法。     

一种用于中药最优配方挖掘的3-阶段选举筛选算法

提出了一种用于挖掘中药最优配方的三阶段选举筛选算法.首先对不同配方的中药新药的临床疗效数据进行可视化.然后,从可视化后的疗效数据曲线中提取若干疗效特征.最后,采用三阶段选举算法筛选新药配方.第一阶段是初选,每一实验样本投票产生指定配方指定指标的特征值.第二阶段是中选,指定配方指定指标的特征值投票产生指定配方指定指标的药效值.第三阶段是终选,每一指标的药效值投票产生指定配方的综合药效值.通过权衡所有配方的综合药效值,就可以找到最优中药配方.实验结果显示该方法对于这类问题是有效的,能较好挖掘出最优中药新药配方,并对新药的临床实验具有指导意义.该方法的潜在应用包括新药开发、风险投资最优组合和基因序列分析等.     

中药化学数据库关联规则的挖掘

数据挖掘是一种新兴的信息处理技术,本文将其中的关联规则运用到中药化学数据的处理,对其中的中医药效、植物科属、化学成分的活性、中药提取物现代药理等数据进行了维间关联规则的挖掘,找到了一系列的强规则,并对这些规则进行了分析,得到了其中有趣的关联规则,同时该关联规则的结果也说明了中药和西药在药效概念上的差异。该结果对于中药现代化,植物化学等相关的研究提供了一种新的思路。     

基于J2EE的中药有效成分化合物数据库的研究与构建(英文)

基于J2EE研究并建立了中药有效成分化合物数据库。该数据库包含了化合物的诸多信息,包括英文名称、物理化学性质、药理活性数据、分子式、分子量、CAS登记号以及其二维化学结构。通过XML作为数据交换格式导出了存储在Word表格中的有效成分化合物数据,并基于ISIS Base构建了中药有效成分化合物数据库。基于该数据库可进行数据挖掘,进而可在中药和西药之间、中药药效和有效成分之间进行关联规则、聚类分析等研究。     

基于SimRank的中药“效-效”相似关系挖掘

中药“效-效”关联分析是中医药研究中最基本也是最重要的问题,对药效判断具有重要意义。该文旨在利用数据挖掘技术,从中药方剂数据中自动挖掘“效-效”相似关系,自动归纳不同药效之间的相似度,提出了基于SimRank方法的“效-效”相似关系挖掘算法。中医专家对算法输出结果的大量验证表明,该算法具有较高的正确率,其中“优良”和“合理”共占70.568%。     

三维荧光二阶校正法直接快速测定血浆样中川芎嗪和阿魏酸含量

本文将三维荧光光谱与二阶校正方法相结合用于人体血浆样中的中药药理活性成分川芎嗪和阿魏酸含量的直接测定.尽管预测样存在血浆内源荧光物质的基体干扰,但由于该方法基于“数学分离”的思路和具有“二阶优势”,仍能对荧光光谱严重重叠的血浆样中的目标分析物进行直接同时定量测定,为川芎嗪和阿魏酸在体内的代谢监控及其药效研究提供了一种新思路.获得的预测样中川芎嗪和阿魏酸的平均回收率分别为(95.7±2.2)％和(100.8±2.5)％.该方法简单、快速,结果可靠.     

红外和近红外光谱法在中药定性分析中的应用

目的:为中药的光谱研究提供参考.方法:综述了近年来红外和近红外光谱法在中药定性分析领域的应用,并对2种光谱技术的特点进行了比较a结果与结论:红外和近红外光谱法具有全面、快速、客观、无损等优点,为中药质量控制提供了新的思路.     

中药药丸称重传感器系统的设计

简述针对中药药丸的快速高精度测量的需求,使用高精度模数转换器和总线通讯技术构成中药药丸称重传感器系统,根据AD7190模数转换器的参数设计了低噪声电路,给出了传感器寄存器的最佳配置参数及数字滤波方法,同时给出了称重传感器系统的精度测试结果.     

中药的药理作用与其无机元素钙含量间关系的研究

本文报告用离子选择电极法测定中药中可溶钙含量的方法。测定结果表明离子选择电极法对中草药中无机元素的研究是一种简单、快速、准确的方法。本实验的平均回收率为92.1％。     

应用易感者-暴露者-感染者-康复者模型对COVID-19的传播及防御措施分析

该文通过易感者-暴露者-感染者-康复者模型分析新型冠状病毒肺炎(COVID-19)在人群中传播的过程,及不同防御措施对疫情曲线的影响,针对结果为疫情的防控提出建议.根据人群接触网络模式对易感者-暴露者-感染者-康复者模型进行改进,加入隔离、中医药干预等模型元素,构建符合新冠肺炎传播特点的数学模型.将影响新型冠状病毒肺炎...     

On-line trust: concepts, evolving themes, a model

Trust is emerging as a key element of success in the on-line environment. Although considerable research on trust in the offline world has been performed, to date empirical study of on-line trust has been limited. This paper examines on-line trust, specifically trust between people and informational or transactional websites. It begins by analysing the definitions of trust in previous offline and on-line research. The relevant dimensions of trust for an on-line context are identified, and a definition of trust between people and informational or transactional websites is presented. We then turn to an examination of the causes of on-line trust. Relevant findings in the human–computer interaction literature are identified. A model of on-line trust between users and websites is presented. The model identifies three perceptual factors that impact on-line trust: perception of credibility, ease of use and risk. The model is discussed in detail and suggestions for future applications of the model are presented.     

Computer use,confidence, attitudes,and knowledge: A causal analysis

This study introduces a casual model which links measures of computer experience, computer-related attitudes, computer-related confidence, and perceived computer-based knowledge. The model is based on the concept of computer literacy, and on an attitude-behavior theory which argues that beliefs lead to attitudes, and that attitudes are an important precursor to behavior. The causal model suggests that computer use has a positive effect on perceived computer self-confidence, as well as on computer-related attitudes. The model hypothesizes that computer attitudes and computer confidence have a positive mutual effect, and that both factors positively effect perceived computer knowledge. Questionnaires were administered to 309 students in Grades 7–12. The theoretical model was tested by structural equation analysis (LISREL) and, as expected, all causal effects, including the reciprocal one, were confirmed. The contribution and relevance of these findings to future educational research and to school practices are discussed.     

Measuring information systems success: models,dimensions, measures,and interrelationships

Since DeLone and McLean (D&M) developed their model of IS success, there has been much research on the topic of success as well as extensions and tests of their model. Using the technique of a qualitative literature review, this research reviews 180 papers found in the academic literature for the period 1992–2007 dealing with some aspect of IS success. Using the six dimensions of the D&M model – system quality, information quality, service quality, use, user satisfaction, and net benefits – 90 empirical studies were examined and the results summarized. Measures for the six success constructs are described and 15 pairwise associations between the success constructs are analyzed. This work builds on the prior research related to IS success by summarizing the measures applied to the evaluation of IS success and by examining the relationships that comprise the D&M IS success model in both individual and organizational contexts.     

Review of rational (total) nonlinear dynamic system modelling,identification, and control

This paper is a summary of the research development in the rational (total) nonlinear dynamic modelling over the last two decades. Total nonlinear dynamic systems are defined as those where the model parameters and input (controller outputs) are subject to nonlinear to the output. Previously, this class of models has been known as rational models, which is a model that can be considered to belong to the nonlinear autoregressive moving average with exogenous input (NARMAX) model subset and is an extension of the well-known polynomial NARMAX model. The justification for using the rational model is that it provides a very concise and parsimonious representation for highly complex nonlinear dynamic systems and has excellent interpolatory and extrapolatory properties. However, model identification and controller design are much more challenging compared to the polynomial models. This has been a new and fascinating research trend in the area of mathematical modelling, control, and applications, but still within a limited research community. This paper brings several representative algorithms together, developed by the authors and their colleagues, to form an easily referenced archive for promotion of the awareness, tutorial, applications, and even further research expansion.     

Design,analysis, set-up fabrication,control, and a novel analytical approach of a levitation prototype for a symmetric shaped object

This paper highlights the design, electromagnetic analysis, system modelling, set-up fabrication, and finally control of an attraction type lab developed levitation prototype. The objectives of this work are parameters' evaluation, for example, force, inductance, and current-air-gap characteristics using a novel analytical model, electromagnetic results, and practical experiments. The FE model has been built using standard packages. A novel permeance function-based approach is developed for the analytical evaluation of parameters. These are verified by actual experiments too with excellent correlation between the sets of results. Agreement between analytical and practical values also show that the modelling is perfect and reliable which further leads to accurate design, fabrication, and implementation of the controller. A simple but reliable controller has been designed, analyzed, and implemented. The performances have been significantly improved. Finally, the steel object has been successfully and steadily levitated in robust condition.     

Usability, quality, value and e-learning continuance decisions

Previous research suggests that an eventual information technology (IT) success depend on both its initial adoption (acceptance) and subsequent continued usage (continuance). Expectancy disconfirmation theory (EDT) has been successfully used to predict users’ intention to continue using information technologies. This study proposed a decomposed EDT model to examine cognitive beliefs and affect that influence users’ continuance decision in the context of e-learning service. The proposed model extended EDT by decomposing the perceived performance component into usability, quality, and value. Research hypotheses derived from this model are empirically validated using the responses to a survey on e-learning usage among 183 users. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.     

Static, Dynamic, and Hybrid Neural Networks in Forecasting Inflation

The back-propagation neural network (BPN) model has been the most popular form of artificial neural network model used for forecasting, particularly in economics and finance. It is a static (feed-forward) model which has a learning process in both hidden and output layers. In this paper we compare the performance of the BPN model with that of two other neural network models, viz., the radial basis function network (RBFN) model and the recurrent neural network (RNN) model, in the context of forecasting inflation. The RBFN model is a hybrid model with a learning process that is much faster than the BPN model and that is able to generate almost the same results as the BPN model. The RNN model is a dynamic model which allows feedback from other layers to the input layer, enabling it to capture the dynamic behavior of the series. The results of the ANN models are also compared with those of the econometric time series models.     

Usability,quality, value and e-learning continuance decisions

Previous research suggests that an eventual information technology (IT) success depend on both its initial adoption (acceptance) and subsequent continued usage (continuance). Expectancy disconfirmation theory (EDT) has been successfully used to predict users’ intention to continue using information technologies. This study proposed a decomposed EDT model to examine cognitive beliefs and affect that influence users’ continuance decision in the context of e-learning service. The proposed model extended EDT by decomposing the perceived performance component into usability, quality, and value. Research hypotheses derived from this model are empirically validated using the responses to a survey on e-learning usage among 183 users. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.