The Solutions for Adjustment and Reconstruction of Water-Drive Surface Systems in the Old Areas of Daqing Oilfield

Introduction 　　Owing to long-time running, more facilities including stations, pipelines, vessels have become corrosive and aged ,some process has grown old, it has exert more burden for the maintenance and repair.Simultaneously, the fluid production rate, oil production rate and water injection rate has changed greatly so that the inflicts and problems from the established surface systems will become more obvious. Energy cost of production and running has increasing continuously. Capacity has been unbalance in systems and areas. 　　……     

Recovery of fluorocarbons in Japan as a measure for abating global warming

The objective of this study is to evaluate the potential for recovering fluorocarbons as measures for the abatement of global warming. In this study, we focused on the three different kinds of fluorocarbons: CFCs, HCFCs and HFCs, and targeted refrigerant use because of the availability of relevant data. We first estimated future fluorocarbon emissions from the targeted appliances; we next compared those emissions in the units of CO₂ equivalent to the level of CO₂ emissions in 1990 from a quantitative point of view. As the result of this study, it was found that fluorocarbon emissions in 1999 and 2010 would be equal to approximately 7 and 3% of the level of CO₂ emissions in 1990 respectively. Moreover, if we implement a 100% recovery rate in every recovery route, we can reduce a large amount of emissions which correspond to approximately 2–5% of the level of CO₂ emissions in 1990, even if we take into account the energy-related CO₂ emissions by the transportation and decomposition of fluorocarbons.     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Magnetic field dependence of shielding current density in Y-Ba-Cu-O rings at 77 K

A method for contactless measurement of the shielding critical current density and its dependence on the external magnetic field is described and analyzed. The obtained values are compared with those measured resistively on two different samples. It is shown that the shielding critical current densityJ _cs and the intergranular transport current densityJ _cr are identical if the measurement conditions are similar. A degradation ofJ _cs measured in the external field with AC ripple has been observed.     

Intelligent identification and control for autonomous guided vehicles using adaptive fuzzy-based algorithms

Fuzzy logic was first suggested as the mechanism by which humans drive cars. This paper addresses the use of fuzzy logic and algorithms towards the intelligent autonomous motion control of land vehicles. To cope with vehicle complexities, internal parametric changes, and with unpredictable environmental effects, the controllers that are presented, whilst heuristic in nature, are self-organizing or self-learning in that they generate automatically by observation an experiential rule base that models the vehicle, and via an appropriate performance index an optimal control rule base that is robust to large parametric changes. The methodology presented is applicable to any complex process which is too difficult to model or control using conventional methods, or which has relied on the experience of a human operator. An overview of fuzzy logic and static fuzzy logic control (akin to expert systems) is provided, together with illustrative examples.