Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

空管系统中键盘快捷功能的研究与实现

目前国内空中交通管制系统人机界面的操作越来越趋于人性化,从可用、能用到好用的人机界面发展过程中,软件提供快捷的功能和方便的操作流程起到了很重要的作用,因此研究软件开发对键盘快捷键的支持就显得尤其重要。本文对可以实现的方法进行比较,分析实现方法的优劣,提出了一种实现键盘快捷功能的方法。     

Hybrid function projective synchronization of chaotic systems with uncertain time-varying parameters via Fourier series expansion

In this paper, the hybrid function projective synchronization (HFPS) of different chaotic systems with uncertain periodically time-varying parameters is carried out by Fourier series expansion and adaptive bounding technique. Fourier series expansion is used to deal with uncertain periodically time-varying parameters. Adaptive bounding technique is used to compensate the bound of truncation errors. Using the Lyapunov stability theory, an adaptive control law and six parameter updating laws are constructed to make the states of two different chaotic systems asymptotically synchronized. The control strategy does not need to know the parameters thoroughly if the time-varying parameters are periodical functions. Finally, in order to verify the effectiveness of the proposed scheme, the HFPS between Lorenz system and Chen system is completed successfully by using this scheme.     

An on-line learning neural controller for helicopters performing highly nonlinear maneuvers

This paper presents an on-line learning adaptive neural control scheme for helicopters performing highly nonlinear maneuvers. The online learning adaptive neural controller compensates the nonlinearities in the system and uncertainties in the modeling of the dynamics to provide the desired performance. The control strategy uses a neural controller aiding an existing conventional controller. The neural controller is based on a online learning dynamic radial basis function network, which uses a Lyapunov based on-line parameter update rule integrated with a neuron growth and pruning criteria. The online learning dynamic radial basis function network does not require a priori training and also it develops a compact network for implementation. The proposed adaptive law provides necessary global stability and better tracking performance. Simulation studies have been carried-out using a nonlinear (desktop) simulation model similar to that of a BO105 helicopter. The performances of the proposed adaptive controller clearly shows that it is very effective when the helicopter is performing highly nonlinear maneuvers. Finally, the robustness of the controller has been evaluated using the attitude quickness parameters (handling quality index) at different speed and flight conditions. The results indicate that the proposed online learning neural controller adapts faster and provides the necessary tracking performance for the helicopter executing highly nonlinear maneuvers.     

一种新的修正恒模算法

阐述了恒模算法(CMA)、修正恒模算法(MCMA)和判决引导(DD)算法的基本原理。针对CMA和MCMA收敛速度慢,固定步长条件下收敛速度和剩余误差之间存在矛盾的缺陷,在分析CMA误差特性的基础上,利用DD算法误差函数的模值和判决器输出构造新的误差函数,提出了一种新的变步长MCMA。新算法在加快收敛速度的同时保持小的剩余误差。仿真结果表明,新算法比CMA和MCMA收敛速度快,均衡输出剩余码间干扰(ISI)小而且能克服相位偏移,具有很好的实用性。     

基于改进蚁群算法的模糊控制器优化设计

研究控制器优化问题,由于模糊控制系统参数无法同时优化,使得系统选择参数困难,使系统控制效果存在一定的缺陷,安全性和可靠性降低。为解决上述问题,提出了一种多种群进化蚁群算法对模糊控制器优化设计。采用懒蚂蚁效应的改进蚁群算法进行优化,在传统蚁群算法的基础上,采用多个种群并行,对算法的初始化、路径构建以及信息素更新改进,并引入到模糊控制器的隶属函数、模糊规则的优化搜索中,搜索出适应于不同控制阶段的模糊控制器参数及控制规则,并进行仿真。仿真结果证明了改进算法对模糊控制器的参数具有良好的搜索速度和精度,使系统有很强的鲁棒性。     

Vague集的新模糊熵

本文指出了现有Vague集模糊熵定义的不足,分析了其存在不足的根本原因,给出了Vague集模糊熵的公理化定义,提出了一种新的Vague集模糊熵的计算方法,并证明了其合理性和有效性。     

嵌入式软键盘UI一致性与功能差异性的研究

为了解决嵌入式WinCE系统所带软键盘按钮小和嵌入式设备触模操作便捷性要求之间矛盾,本文提出设计软键盘代替WinCE系统所带软键盘。为了解决嵌入式系统中多个数据输入的软键盘界面与嵌入式系统资源有限的矛盾,在设计中,提出了一种将软键盘界面与增加数据功能、删除数据功能、显示数据功能、数据合法性检查功能等键盘处理逻辑分离的技术,不同功能模块调用统一软键盘界面,实现了软键盘UI一致性和功能差异性,从而节省了系统资源;此外,为了减少软键盘按钮数,在小触模屏条件下触模按钮做得更大,提出了系统附加数据单位字符技术,这种技术也提高了用户数据输入速度。综合运用这些技术,完成了基于WinCE平台软键盘开发研制,实际应用表明提高了操作便捷性。     

Parallel depth first search. Part II. Analysis

This paper presents the analysis of a parallel formulation of depth-first search. At the heart of this parallel formulation is a dynamic work-distribution scheme that divides the work between different processors. The effectiveness of the parallel formulation is strongly influenced by the work-distribution scheme and the target architecture. We introduce the concept of isoefficiency function to characterize the effectiveness of different architectures and work-distribution schemes. Many researchers considered the ring architecture to be quite suitable for parallel depth-first search. Our analytical and experimental results show that hypercube and shared-memory architectures are significantly better. The analysis of previously known work-distribution schemes motivated the design of substantially improved schemes for ring and shared-memory architectures. In particular, we present a work-distribution algorithm that guarantees close to optimal performance on a shared-memory/-network-with-message-combining architecture (e.g. RP3). Much of the analysis presented in this paper is applicable to other parallel algorithms in which work is dynamically shared between different processors (e.g., parallel divide-and-conquer algorithms). The concept of isoefficiency is useful in characterizing the scalability of a variety of parallel algorithms.This work was supported by Army Research Office Grant No. DAAG29-84-K-0060 to the Artificial Intelligence Laboratory, and Office of Naval Research Grant N00014-86-K-0763 to the Computer Science Department at the University of Texas at Austin.     

The Landscape of microRNAs in βCell: Between Phenotype Maintenance and Protection

Diabetes mellitus is a group of heterogeneous metabolic disorders characterized by chronic hyperglycaemia mainly due to pancreatic β cell death and/or dysfunction, caused by several types of stress such as glucotoxicity, lipotoxicity and inflammation. Different patho-physiological mechanisms driving β cell response to these stresses are tightly regulated by microRNAs (miRNAs), a class of negative regulators of gene expression, involved in pathogenic mechanisms occurring in diabetes and in its complications. In this review, we aim to shed light on the most important miRNAs regulating the maintenance and the robustness of β cell identity, as well as on those miRNAs involved in the pathogenesis of the two main forms of diabetes mellitus, i.e., type 1 and type 2 diabetes. Additionally, we acknowledge that the understanding of miRNAs-regulated molecular mechanisms is fundamental in order to develop specific and effective strategies based on miRNAs as therapeutic targets, employing innovative molecules.