Application of symbolic algebra to the generation of coordinate transformations

In this paper we present tools for automatic generation of generalized (variable and terrain-following) coordinate transformations and its use in numerical models of atmospheric flows. Such methodology should be competitive with the more commonly employed nested grid schemes. We discuss the symbolic (computer) algebra program for analytical calculation of Christoffel symbols, metric tensor and other geometrical objects describing a transformation. An example, related to the numerical modeling of mesoscale flows, is given. This example shows how coupled terrain-following and stretching transformation can be easily created. The possible application of such methodology in numerical modeling of air pollution on cirrus clouds is briefly discussed.     

Adaptation and learning in control of voluntary movement by the central nervous system

In order to control voluntary movements, the central nervous system must solve the following three computational problems at different levels: (1) the determination of a desired trajectory in visual coordinates; (2) the transformation of its coordinates into body coordinates; and (3) the generation of motor command. Concerning these problems, relevant experimental observations obtained in the field of neuroscience are briefly reviewed. On the basis of physiological information and previous models, we propose computational theories and a neural network model which account for these three problems. (1) A minimum torque-change model which predicts a wide range of trajectories in human multi-joint arm movements is proposed as a computational model for trajectory formation. (2) An iterative learning scheme is presented as an algorithm which solves the coordinate transformation and the control problem simultaneously. This algorithm can be regarded as a Newton-like method in function spaces. (3) A neural network model for generation of motor command is proposed. This model contains internal neural models of the motor system and its inverse system. The inverse-dynamics model is acquired by heterosynaptic plasticity using a feedback motor command (torque) as an error signal. The hierarchical arrangement of these neural networks and their global control are discussed. Their applications to robotics are also discussed.     

中央空调冷冻水系统的神经PID控制

在对神经网络PID控制器的设计中,利用神经网络对PID控制器参数kp,ki,kd的在线整定与调整,实现对中央空调冷冻水变流量的控制,使系统具有良好的稳态性能与控制精度。     

Mechanisms shaping fast excitatory postsynaptic currents in the central nervous system.

How different factors contribute to determine the time course of the basic element of fast glutamate-mediated excitatory postsynaptic currents (mEPSCs) in the central nervous system has been a focus of interest of neurobiologists for some years. In spite of intensive investigations, these mechanisms are not well understood. In this review, basic hypotheses are summarized, and a new hypothesis is proposed, which holds that desensitization of AMPA receptors plays a major role in shaping the time course of fast mEPSCs. According to the new hypothesis, desensitization shortens the time course of mEPSCs largely by reducing the buffering of glutamate molecules by AMPA receptors. The hypothesis accounts for numerous findings on fast mEPSCs and is expected to be equally fruitful as a framework for further experimental and theoretical investigations.     

预置旋转正交坐标系测量精度分布解析

预置旋转正交坐标系在姿态测量时可增强原始信号幅度,较大地提高了姿态测量的总体精度.通过解算传感器三轴相对误差公式的方法,对预置旋转正交坐标系测量精度分布进行深入分析,研究了预置旋转正交坐标系姿态测量各区域的精度分布特征.图例表明,三轴相对误差在大角度井斜均存在极值点,并且三轴传感器输出相对误差随井斜和工具面角变化而变化.在小角度姿态测量时利用预置旋转的正交坐标系是比较理想的.     

Analysis of the stability of nonlinear regression models to errors in measured data

In order to reconstruct a nonlinear dependence of the refractive index of a medium on the wavelength, a set of inductively generated models for choosing the optimal one is considered. An algorithm for the inductive generation of admissible nonlinear models is applied. A criterion for determining the error in the coefficients of the generated models, which is referred to as stability, and a method for estimating the stability of the solution are proposed. The results of numerical simulation on the data obtained in an experiment on determining the composition of a mixture from its total dispersion are presented.     

Modeling and querying graphical representations of statistical data

Although pictorial renditions of statistical data are ubiquitous, few techniques and standards exist to exchange, search and query these graphical representations. We present several improvements to human–graph interaction including (i) a new approach to manage statistical graph knowledge by semantic annotation of graphs that bridges the gap between Web 2.0 social tagging and formal, logic-based approaches, (ii) knowledge management and discovery across a non-trivial graph knowledge base and (iii) sophisticated question answering that requires background knowledge.     

SDN框架下不良数据计算机网络管理系统设计

近年来,随着互联网的飞速发展,网络信息交互量不断增大。各类不良网络交互信息数据充斥着网络交互空间,给网络社交秩序造成破坏。为此,一系列网络不良数据管理系统孕育而出。通过长期实践发现,传统不良数据计算机网络管理系统的管理方式存在不良数据动态检测性不强、不良信息数据内容识别度低、不良数据管理逻辑性差等问题。通过与SDN框架的优势相结合,提出SDN框架下不良数据计算机网络管理系统设计。采用NVR数据量交互模块、数据特征DNA内容识别算法与大数据统筹规划模块,对传统不良数据管理系统方式中存在的问题进行解决。通过实验证明,提出的SDN框架下不良数据计算机网络管理系统比传统的数据管理系统,在不良数据识别、检测、统计、管理等方面上具有绝对优势。     

SENEX: a computer-based representation of cellular signal transduction processes in the central nervous system

The SENEX project is exploring knowledge representation in the neurobiology of ageing through object-oriented programming. SENEX is built from a classification structure of biologic entities and significant relationships among them. For example, an enzyme is an entity and an enzymatic reaction is a relationship among enzyme, cofactor(s), substrate(s) and product(s). There are currently 2600 classes of entities and 50 classes of relationships in SENEX. The class structure serves several functions. One function is to interrelate general and specific categories of molecular and morphologic entities. For example, tyrosine kinase and serine/threonine kinase are specific types of the more general class of protein kinase enzymes. Another function of the class structure is to serve as a network through which inheritance of attributes may occur. For example, the attribute 'subunits' is inherited by all subclasses of the general class multisubunit protein. Information may be accessed through links established in the class structure and through links relating one object as part of another. Relationships form the basis of separate modules within SENEX. This paper describes the types of relationships currently used and planned in the representation of age-related changes in cellular signal transduction processes of mammalian central nervous systems. We also describe tools for specific retrieval of relationships and for tracing links in complex reaction cascades. Application of these tools to identifying possible signal transduction pathways to guide further exploration through experimentation is discussed.     

中心导航系统终端地图预取和更新策略研究

为解决中心导航系统终端通过网络下载电子地图时,网络延时问题对终端地图实时显示的影响,根据空间相关性原理,提出了一种电子地图数据的预取和更新策略.该策略采用对电子地图分块传输和分块存储方法,对地图数据进行预取,并且使用二级缓存的方法,提高地图显示效率.仿真实验和实际车载实验结果表明,在CDMA的数据链路性能条件下,该预取和更新策略可以保证中心导航系统车载终端地图显示的实时性.     

A note on the justification of landsat data transformations

This paper discusses the mathematical justification for Landsat data transformations. The results are based upon an atmospheric radiation transfer equation given by Turner (5). Several proposed data transformations are discussed and evaluated in light of these justifications.     

Synaesthesia and cycling data art: towards cross-modal representations of self-tacking cycling data

This paper develops ideas around cycling as art practice. The questions at the heart of it revolve around how new data technologies enable us to represent such experiences as artworks. Recent research in neuroscience has begun to establish the ways in which modes of perception are processed in the brain. Related research suggests that Synaesthesia may be caused by a genetic mutation that results in a ‘cross wiring’ of these modes of perception. Within the arts there is a long history of exploration around synaesthesia, ideas that are becoming relevant again particularly in relation to the growth in personal data. Representing sensations and transferring them from one mode to another offers a way to handle some of this data and potentially say new things about our experiences. The author explores these ideas through artworks made using data from cycling to investigate the visualization of this experience.     

Analytic determination of workspace and singularities in a parallel pointing system

This paper studies a parallel pointing system, named U‐2PUS, used in biomechanic and aerospace applications. In the literature, U‐2PUS position analysis has already been solved in closed form, whereas simple and efficient tools to address workspace determination and singularity locations are still lacking. In this paper, the analytic expression of the U‐2PUS workspace is derived, and a bidimensional representation of the workspace is proposed. The U‐2PUS mobility analysis is addressed, and a singularity locus analytic expression, explicitly containing the manipulator geometric parameters and the end‐effector orientation parameters, is derived. Moreover, it is shown that the U‐2PUS singularity locus can be represented by curves (singularity curves) on a Cartesian plane having the U‐2PUS generalized coordinates on the coordinate axes. Finally, the presented singularity conditions are geometrically interpreted. © 2002 John Wiley & Sons, Inc.     

数据采集和智能数据处理系统的分析和设计

结合广东核电合营公司岭澳核电站1、2号两台机组采用的KIT工业过程数据采集系统,对该系统的功能和应用程序接口软件的使用进行了分析和研究,开发了基于Web的实时数据采集和在线数据发布和监控系统,并讨论了基于神经网络技术的智能数据处理系统在核电站发电功率预测中的应用。     

A survey of methods for data fusion and system adaptation using autonomic nervous system responses in physiological computing

Physiological computing represents a mode of human–computer interaction where the computer monitors, analyzes and responds to the user’s psychophysiological activity in real-time. Within the field, autonomic nervous system responses have been studied extensively since they can be measured quickly and unobtrusively. However, despite a vast body of literature available on the subject, there is still no universally accepted set of rules that would translate physiological data to psychological states. This paper surveys the work performed on data fusion and system adaptation using autonomic nervous system responses in psychophysiology and physiological computing during the last ten years. First, five prerequisites for data fusion are examined: psychological model selection, training set preparation, feature extraction, normalization and dimension reduction. Then, different methods for either classification or estimation of psychological states from the extracted features are presented and compared. Finally, implementations of system adaptation are reviewed: changing the system that the user is interacting with in response to cognitive or affective information inferred from autonomic nervous system responses. The paper is aimed primarily at psychologists and computer scientists who have already recorded autonomic nervous system responses and now need to create algorithms to determine the subject’s psychological state.     

Analysis and refinement of software test data adequacy properties

Test data adequacy criteria are standards that can be applied to decide if enough testing has been performed. Previous research in software testing has suggested 11 fundamental properties which reasonable criteria should satisfy if the criteria make use of the structure of the program being tested. It is shown that there are several dependencies among the 11 properties making them questionable as a set of fundamental properties, and that the statements of the properties can be generalized so that they can be appropriately analyzed with respect to criteria that do not necessarily make use of the program's structure. An analysis that shows the relationships among the properties with respect to different classes of criteria which utilize the program structure and the specification in different ways is discussed. It is shown how the properties differ under the two models in order to maintain consistency that the dependencies are largely a result of five very weak existential properties, and that by modifying three of the properties, these weaknesses can be eliminated. The result is a reduced set of seven properties, each of which is strong from a mathematical perspective     

An investigation of the sensitivity of DEA to data errors

The predictive value of a common measure of efficiency and the robustness of the data envelopment analysis (DEA) technique is examined when statistical noise is present in the data. Inferences are drawn from a hypothetical example regarding the potential limitations of the efficiency measure and pitfalls in both the single- and multi-stage applications of DEA. We propose a simple procedure to investigate the robustness of DEA results. The procedure maintains the relative computational simplicity of DEA and is easy to apply and interpret. Using this procedure, we examine the robustness of the results reported in two published DEA studies and find that, indeed, pitfalls occur in practical applications. We conclude with recommendations for researchers applying the technique and implications for managers.     

Validating criteria with imprecise data in the case of trapezoidal representations

We are interested in the issue of determining an alternative’s satisfaction to a criterion when the alternative’s associated attribute value is imprecise. We introduce two approaches to the determination of criteria satisfaction in this uncertain environment, one based on the idea of containment and the other on the idea of possibility. We are particularly interested in the case in which the imprecise data is expressed in terms of a trapezoidal type distribution. We provide an algorithmic solution to this problem enabling it to be efficiently implemented in a digital environment. A number of examples are provided illustrating our algorithms.