unified 和 uniform 的区别

tsingever 2006-10-28 10:54:15

计算机中很多术语是统一....,不知道何时用 unified,何时用uniform,望指教!

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startech 2006-11-06

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劫分~

dashi 2006-10-29

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The platooning of connected and automated vehicles has the potential to significantly benefit the road traffic, including enhancing highway safety, improving traffic capacity, and reducing fuel consumption. This paper presents a four-component analysis framework for platoon systems from a networked control perspective, including a literature review by network awareness, unified models of key components, and two application cases for controller synthesis. The networked control perspective naturally decomposes a platoon into four interrelated components, namely, 1) node dynamics (ND), 2) information flow topology (IFT), 3) formation geometry (FG), and 4) distributed controller (DC). The existing literature is categorized under this framework and analyzed according to the component features. The unified mathematical models are derived for platoons with linear dynamics and distributed controllers. As a case study, a distributed controller synthesis method is introduced for homogeneous platoons, which guarantees the internal stability in the presence of a broad class of topologies with/without uniform time-delays. The effectiveness of the proposed method is demonstrated using numerical simulations

The Road Accident Emergency Response System is meant to mitigate the consequences of road accidents and other emergencies on the roads by reducing the time required to report such accidents to emergency services. This System is called "ERA-RB" in the Republic of Belarus, "EVAK" in the Republic of Kazakhstan and "ERA-GLONASS" in the Russian Federation. The System is analogous to the European eCall System currently under development, and is harmonised with it in regard to its main functional features (the use of in-band modem as the main data transmission tool; unified content and format of mandatory data transmitted in the minimum set of data pertaining to road accidents; uniform procedures for initiation and termination of duplex voice connection with the persons in the vehicle cabin, etc.)

Pentaho Data Integration (PDI) is a flexible tool that allows you to collect data from disparate sources such as databases, files, and applications, and turn the data into a unified format that is accessible and relevant to end users. PDI provides the Extraction, Transformation, and Loading (ETL) engine that facilitates the process of capturing the right data, cleansing the data, and storing the data using a uniform and consistent format

This paper introduces concept lattice and granular computing into ontology learning, and presents a unified research model for ontology building, ontology merging and ontology connection based on the domain ontology base in different granulations. In this model, as the knowledge in the lowest and most basic level, the domain ontology base is presented firstly, which provides a uniform technology for ontology learning on the whole; secondly, in order to better understand problems rather than be o

Foreword Author's Biographical Information Part A—General Theory Chapter 1—Learning Algorithms for Neuro-Fuzzy Networks 1 Introduction 2 Neuro-Fuzzy Networks 2.1 The Conventional Fuzzy Model 2.2 From Fuzzy to Neuro-Fuzzy 2.3 Initialization 2.4 Training Procedure 3 Weight identification for Φ2 3.1 Gradient Descent 3.2 Least Square Method 3.3 Recursive Least Square Method 4 Optimisation of Membership Functions 4.1 First Order Approximation of Gradient 4.2 Random Optimization 5 Examples 5.1 Non Differentiable NFN 5.2 Differentiable NFN 6 Conclusion References Chapter 2—Towards a Unified Theory of Intelligent Autonomous Control Systems 1 Introduction 2 State of the Art and Future Challenges 2.1 Three views of what are the most important robotic issues 2.2 Some Pros and Cons of the Available Methodologies 3 Adaptive Systems and the Dual Control Problem 3.1 Identification vs. Optimization in Changing Environments 4 A Systemic Approach to Behavioural Specification of Intelligent Systems 4.1 A Conceptual Framework for Describing and Synthesizing Actions of an Intelligent System 5 Behavioural Specification of the Activities of a System of Interacting Actors 5.1 Models of Actors interacting with their Environments 6 Fuzzification of Formal Models of Adaptive Autonomous Control Systems 6.1 The Effects of Imprecision and Uncertainty 6.2 Fuzzification of Power Sets and Relational Systems 7 Fuzzy identification 8 Introducing Control Hierarchies

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