Effect of gas mixing ratio on gas-phase composition and etch rate in an inductively coupled CF4/Ar plasma

In this work, we carried out investigations aimed at understanding the effect of gas mixing ratio on plasma parameters, gas phase composition and etch rate in CF₄/Ar inductively coupled plasma. For this purpose, a combination of experimental methods and modelling was used. Experiments showed that electron temperature and electron density are not very sensitive to variations of Ar content in CF₄/Ar plasma. From a zero-dimensional plasma model, the densities of both neutral and charged particles change monotonically. The analysis of surface kinetics based on an ion-assisted etching mechanism showed the possibility of non-monotonic etch rate behaviour due to a concurrence of chemical and physical etching pathways.     

Filtration of Non-Newtonian Hydrocarbon Fluid in a High-Frequency Electromagnetic Field

The paper gives the results of experimental investigations of the initial pressure gradient of bituminous oil and the time dependences of variation of the temperature in a formation model and of the well production rate in a microwave-frequency electromagnetic field. The effect of strong decay of the non-Newtonian properties of bituminous oil is revealed. The nonuniformity of temperature distribution over the formation thickness is demonstrated, which depends on the initial production rate of the well and on the duration of stimulation of the bottom-hole zone of formation.     

黑岱沟露天矿重型汽车预防性维修的探讨

通过对黑岱沟露天煤矿运输设备出动率调查,初步分析了目前主要运输设备的现状以及存在问题的原因和影响因素,就加大预防性维修的比重,实行全面的预防性维修制度提出了一些看法。     

东方N-18250-2型凝汽器胶球清洗系统改造

对湘潭电厂存在已久的胶球清洗装置收球率低的问题进行了深入探讨，结合电厂对胶球清洗系统的改造、试验过程，分析并提出了影响胶球清洗装置清洗效果及收球率的诸多原因及其解决方法。     

德国联邦物理技术研究院(PTB)气体微流量计量评介

在真空技术应用中 ,高精度气体微流量计用于连续膨胀法校准系统压力的产生、漏孔漏率的测量以及真空泵抽速的测定。PTB先后研制了三代气体微流量计 ,第一代为手动型 ,第二代为半自动型 ,第三代为全自动型。本文详细介绍了PTB研制的气体微流量计的性能和特点 ,并介绍了气体微流量计在真空漏孔的漏率测量方面的应用。另外 ,还介绍了PTB最近研制的大气压力下漏孔漏率测量系统的性能和特点     

BFG的热值及温度与0号机出力和效率的关系

分析煤气温度、干煤气热值和湿煤气热值之间的关系，得到0号机组长期达不到额定出力和效率的原因，在此基础上提出解决问题的方法。     

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.     

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.