论家庭教育中儿童人格的塑造与培养

父母及家庭环境对儿童人格形成与发展具有十分重要的影响。父母要以身示范,营造和睦、健康、向上的家庭氛围。在儿童人格塑造和培养中,要十分重视智力因素的培养,特别注意早期智力与创造力的开发,重视社会适应能力的培养,包括融入集体生活的能力、人际适应能力和环境适应能力等。     

线性回归分析与能源需求预测

结合实例介绍了回归模型方法在能源预测中的应用，具体地讨论了最简单、最基本的直线回归模型结构及参数估计方法，对于其他一些曲线回归模型则可通过变量代换转化为直线回归模型。     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

Predictability and model selection in the context of ARCH models

Most of the methods used in the ARCH literature for selecting the appropriate model are based on evaluating the ability of the models to describe the data. An alternative model selection approach is examined based on the evaluation of the predictability of the models in terms of standardized prediction errors. Copyright © 2005 John Wiley & Sons, Ltd.     

黄酮类天然产物13C NMR数据的计算机检索和辅助解析(Ⅱ)黄酮类天然产物的13C NMR数据规律及其在智能解析中的应用

本文通过对大量的黄酮类化合物¹³C NMR图谱的分析和研究,总结了不同类型的黄酮类化合物的¹³C NMR图谱特征及化学位移规律.对影响黄酮类化合物结构骨架上不同位置碳原子化学位移的因素进行了分析,建立了用于黄酮类天然产物¹³C NMR图谱智能解析的知识库.     

Non-Parametric Regression Methods

The nature of the financial time series is complex, continuous interchange of stochastic and deterministic regimes. Therefore, it is difficult to forecast with parametric techniques. Instead of parametric models, we propose three techniques and compare with each other. Neural networks and support vector regression (SVR) are two universally approximators. They are data-driven non parametric models. ARCH/GARCH models are also investigated. Our assumption is that the future value of Istanbul Stock Exchange 100 index daily return depends on the financial indicators although there is no known parametric model to explain this relationship. This relationship comes from the technical analysis. Comparison shows that the multi layer perceptron networks overperform the SVR and time series model (GARCH).     

斜坡变形破坏的预测及防护

通过对斜坡变形破坏和影响因素的研究，探讨工程建设中斜坡变形破坏的预测及防护。     

变速齿轮传动系统最佳轴向结构布局智能设计的推理机制

本文通过对变速齿轮传动系统轴向结构布局设计规律的研究,提出了一种适合于该类问题的知识表达方式,将改进后的带有启发函数的最佳优先搜索方法引入到该问题的求解中,使得含有多重搜索空间以及带有一定约束的设计问题统一在同一搜索策略下。根据本文提出的方法,用PROLOG语言建造的推理机,通过对实际问题的考证,证明该方法在解决传动结构自动设计上是行之有效的,并且在推理机制上成功地体现了设计过程中反复设计与优化设计的功能特征.     

微机字处理软件CAI开发方法的研究

本文阐述了研究计算机软件ＣＡＩ开发方法学的意义，并介绍了字处理软件Ｗｏｒｄｓｔａｒ的教学软件的开发方法．     

临界等温线的推算──几个立方型状态方程的比较

对ＰＴ方程等几个立方型状态方程描述氩的临界等温线的能力作比较研究。在临界压力以下区域．ＰＴ方程、ＨＳ－ＳＲＫ方程和ＳＲＫ方程推算精度较好，ＡＡＤ＜０．４％。在临界压力以上区域，所讨论的五个方程都不能提供具有合理精度的描述。