测井曲线在识别陈家庄凸起北部缓坡带层序边界中的应用

针对陈家庄凸起北部缓坡带特殊的沉积、构造特征．应用测井曲线来识别层序边界。应用自然电位和电阻率测井曲线的组合来确定层序边界，可根据自然电位基线强烈偏移、视电阻率的突增或突减等异常现象的出现来判别；利用声波时差和电阻率曲线的叠合，在层序边界处常对应△logR的低谷值；应用累计倾角图来识别层序边界优于常规的地层倾角．累计倾角的一阶导数更能突出异常点的位置。测井曲线应用于识别层序边界，有其自身的优势，在该研究区取得了较好的效果。     

Learning Organizations in Construction

The transformation of organizations from production-oriented entities to proactive learning entities that continuously leverage the knowledge of the workforce is a primary objective of management researchers. This focus has significant relevance to the construction industry where production-related research has predominantly overshadowed organizational development research. As one effort to change this emphasis, the writers present a research effort designed to study current organization learning techniques and technologies fielded by organizations both inside and outside of the construction industry. Through a series of exploratory case studies, the writers developed a maturity model together with the Construction Industry Institute that provides construction organizations with a framework for developing a learning organization culture. The maturity model focuses on learning organization characteristics of leadership, processes and infrastructure, communication/collaboration, education, and culture at the organization, community, and individual levels. This paper introduces the results of that effort including a presentation of the learning organization maturity model, framework application, and the overall characteristics of a learning organization.     

ISIS全局优化多道反演技术在墩2块岩性油藏描述中的应用

为进一步落实墩2块戴一段岩性油藏成藏规模及分布规律，针对该储层薄、横向变化快的特点，利用ISIS全局优化多道反演技术，对该构造区岩性储层进行了精细描述，较好的预测出戴一段储层平面分布规律。     

电梯门机控制系统的运行曲线设计

为了实现电梯轿厢门的开门和关门快速且平稳地运行，介绍了一种基于高性能微型机的门机控制系统结构和门位移的检测原理，以门位移量作为控制系统的反馈量，对门机运行速度进行了分区设计。在高速附近的变化区，门机速度匀速变化时，进行了门机开门和关门控制曲线的计算，推导出运行位移与门机速度具有二次曲线的关系，进而对微型机控制的软件流程进行了设计，达到了门机高低速运行的平稳过渡。最后，给出了实际运行系统的主电路电压波形。     

Learning Automata from Ordered Examples

Connectionist learning models have had considerable empirical success, but it is hard to characterize exactly what they learn. The learning of finite-state languages (FSL) from example strings is a domain which has been extensively studied and might provide an opportunity to help understand connectionist learning. A major problem is that traditional FSL learning assumes the storage of all examples and thus violates connectionist principles. This paper presents a provably correct algorithm for inferring any minimum-state deterministic finite-state automata (FSA) from a complete ordered sample using limited total storage and without storing example strings. The algorithm is an iterative strategy that uses at each stage a current encoding of the data considered so far, and one single sample string. One of the crucial advantages of our algorithm is that the total amount of space used in the course of learning for encoding any finite prefix of the sample is polynomial in the size of the inferred minimum state deterministic FSA. The algorithm is also relatively efficient in time and has been implemented. More importantly, there is a connectionist version of the algorithm that preserves these properties. The connectionist version requires much more structure than the usual models and has been implemented using the Rochester Connectionist Simulator. We also show that no machine with finite working storage can iteratively identify the FSL from arbitrary presentations.     

Why is science difficult to learn? Things are seldom what they seem

Abstract The difficulties of learning science are related to the nature of science itself and to the methods by which science is customarily taught without regard to what is known about children's learning. An information processing model is proposed to guide thinking and research in this area.     

铝钛双金属板KR曲线测定

利用宽３００ｍｍ、长／宽＝１的横向ＣＴＴ试样对国产铝钛双金属板做了常规力学性能测定，并按航标测定了ＫＲ曲线，经过柔度法和Ｋ值计算，分别测得了ＫＲｉ和ａｉ数据，确定了临界的ＫＣ值通过性能数据对比，研制的材料达到了进口料的性能要求。     

Pruning Algorithms for Rule Learning

Pre-pruning and Post-pruning are two standard techniques for handling noise in decision tree learning. Pre-pruning deals with noise during learning, while post-pruning addresses this problem after an overfitting theory has been learned. We first review several adaptations of pre- and post-pruning techniques for separate-and-conquer rule learning algorithms and discuss some fundamental problems. The primary goal of this paper is to show how to solve these problems with two new algorithms that combine and integrate pre- and post-pruning.     

产量递减规律的诊断方法

传统的Arps产量递减分析方法要求事先选定递减规律的初始时间、初始产量及初始递减率,事实上这些参数是很难确定的。实际应用时不得不人为地加以臆断而使得此方法带有不确定性.为此提出了产量递减规律的诊断方法。应用诊断曲线很容易确定递减规律的模型参数,克服常规方法的不足。通过选用参考时间、参考产量和参考递减率,使得递减分析方法具有一定的灵活性和优越性、该方法简便、实用。     

发动机扭矩与转速关系经验公式试验研究

在对发动机外特性曲线扭矩与转速实验数据分析的基础上，对原有的经验公式进行了分析、改进，提出了新的经验公式．由这一经验公式所计算的数值，在最大扭矩与最大功率点之间，可与实验数据拟合得很好．与原经验曲线相比，新经验曲线与实验曲线的离差可下降50％以上．