Neural network payload estimation for adaptive robot control

A concept is proposed for utilizing artificial neural networks to enhance the high-speed tracking accuracy of robotic manipulators. Tracking accuracy is a function of the controller's ability to compensate for disturbances produced by dynamical interactions between the links. A model-based control algorithm uses a nominal model of those dynamical interactions to reduce the disturbances. The problem is how to provide accurate dynamics information to the controller in the presence of payload uncertainty and modeling error. Neural network payload estimation uses a series of artificial neural networks to recognize the payload variation associated with a degradation in tracking performance. The network outputs are combined with a knowledge of nominal dynamics to produce a computationally efficient direct form of adaptive control. The concept is validated through experimentation and analysis on the first three links of a PUMA-560 manipulator. A multilayer perceptron architecture with two hidden layers is used. Integration of the principles of neural network pattern recognition and model-based control produces a tracking algorithm with enhanced robustness to incomplete dynamic information. Tracking efficacy and applicability to robust control algorithms are discussed.     

Approximate channel identification via δ‐signed correlation

A method of approximate channel identification is proposed that is based on a simplification of the correlation estimator. Despite the numerical simplification (no multiplications or additions are required, only comparisons and an accumulator), the performance of the proposed estimator is not significantly worse than that of the standard correlation estimator. A free (user selectable) parameter moves ‘smoothly’ from a situation with small sum‐squared channel estimation error but hard‐to‐identify channel peaks, to one with a larger sum‐squared estimation error but easy‐to‐identify channel peaks. The proposed estimator is shown to be biased and its behaviour is analysed in a number of situations. Applications of the proposed estimator to sparsity detection, symbol timing recovery and to the initialization of blind equalizers are suggested. Copyright © 2002 John Wiley & Sons, Ltd.     

Intelligent handling of data by integration of commonsense reasoning

Any intelligent problem solving system should be able, given the known data on a case, to decide whether some item of information is true, false or unknown. In this paper the way in which various forms of commonsense reasoning can be integrated to provide such decisions is described. To this end three structural types of knowledge defined over data, and four strategies for exploiting these structures, are identified. ‘Decide-Status’ integrates the reasoning strategies into a task frame. This frame structure not only integrates the reasoning but also affords the appropriate facilities for providing strategic justifications for its conclusions, if required.     

Maturation ponds, rock filters and reedbeds in the UK: statistical analysis of winter performance.

Wastewater treatment technologies suitable for serving large populations are generally reliable and reasonably cost-effective, yet they are almost always financially inappropriate for small communities (< 2,000 p.e.). Comparative cost data suggests that waste stabilization ponds should be an attractive option for small communities, yet perceptions relating to land costs, climate and effluent quality have limited their application in the UK. This paper details typical UK land costs, climate and winter performance data for a pilot-scale waste stabilization pond with various upgrading technologies: system A, two tertiary maturation ponds in series; B, two tertiary maturation ponds in series followed by a reed bed channel; C, a control rock filter; D, an aerated rock filter; and E, a constructed wetland. System D was found to perform best, closely followed by system B.     

THE LOW CYCLE IMPACT FATIGUE PROPERTIES OF PEARLITIC PLAIN CARBON STEELS

The results of Stan ton and Bairstow (1908) have been reanalyzed to yield information on the composition dependence of the low cycle impact fatigue properties of pearlitic plain carbon steels. It has been found that the energy absorbed per impact, E_i, and the number of impacts are failure, N_f, are related by the equation: In this equation q is determined by the carbon, manganese and silicon contents of the steel; E_o is the impact endurance limit; and C and D are constants. The curve represented by this equation intersects that representing the Johnson-Keller high cycle impact fatigue equation at a value of log_eN_f equal to 1/C. Thus, the transition from low to high cycle impact fatigue occurs at this value of log_eN_f.     

封装与测试——解决功率电子器件的热问题

纽约州立大学Buffalo分校电子封装实验室正在为美国海军开发新型的功率电子封装，在一些极端苛刻的工作条件下（比如在军舰和战机上）．它们能够解决大电流密度、高温和大的温度梯度所引起的种种问题。这类功率电子封装还有可能很快进入民用产品。     

Neural components of social evaluation.

Evaluative responses appear to involve 2 seemingly distinct sets of processes: those that are automatically activated and others that are more consciously controlled. Using functional magnetic resonance imaging, the authors investigated the brain systems associated with automatic and controlled evaluative processing. Participants made either evaluative (good-bad) or nonevaluative (past-present) judgments about famous names. Greater amygdala activity was observed for names rated as "bad" relative to those rated as "good," regardless of whether the task directly involved an evaluative judgment (good-bad) or not (past-present). Good-bad judgments resulted in greater medial and ventrolateral prefrontal cortex (PFC) activity than past-present judgments. Furthermore, there was greater ventrolateral PFC activity in good-bad judgments marked by greater ambivalence. Together, these findings indicate a neural distinction between processes engaged for automatic and controlled evaluation. Whereas automatic processes are sensitive to simple valence, controlled processes are sensitive to attitudinal complexity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The integrated academic information management system at Columbia-Presbyterian Medical Center.

Over the past seven years, Columbia-Presbyterian Medical Center has been planning and implementing an integrated academic information management system. Accomplishments to date include establishing an institutional information architecture, installing a campus-wide network of workstations, recruiting the staff needed to develop and implement the system, and developing various applications. This paper presents the rationale and steps involved in these accomplishments, as well as data on use of the system so far.