Preface Part I. Turbulence: 1. Introduction 2. Coherent structures 3. Proper orthogonal decomposition 4. Galerkin projection Part II. Dynamical Systems: 5. Qualitative theory 6. Symmetry 7. One-dimensional 'turbulence' 8. Randomly perturbed systems Part III. 9. Low-dimensional Models: 10. Behaviour of the models Part IV. Other Applications and Related Work: 11. Some other fluid problems 12. Review: prospects for rigor Bibliography.

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Turbulence, Coherent Structures, Dynamical Systems and Symmetry

A survey of models, analysis tools and compensation methods for the control of machines with friction

Configuration of the computing and communications systems found at home and in the workplace is a complex task that currently requires the attention of the user. Researchers have begun to examine computers that would autonomously change their functionality based on observations of who or what was around them. By determining their context, using input from sensor systems distributed throughout the environment, computing devices could personalize themselves to their current user, adapt their behaviour according to their location, or react to their surroundings. The authors present a novel sensor system, suitable for large-scale deployment in indoor environments, which allows the locations of people and equipment to be accurately determined. We also describe some of the context-aware applications that might make use of this fine-grained location information.

/pdf/a-new-location-technique-for-the-active-office-5bygv7mxxa.pdf

A new location technique for the active office

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

* An evolutionary approach provides a unifying theme 
* Thorough coverage of important AI ideas, old and new
* Frequent use of examples and illustrative diagrams
* Extensive coverage of machine learning methods throughout the text
* Citations to over 500 references
* Comprehensive index

Table of Contents

1 Introduction
2 Stimulus-Response Agents
3 Neural Networks 
4 Machine Evolution 
5 State Machines 
6 Robot Vision 
7 Agents that Plan 
8 Uninformed Search 
9 Heuristic Search 
10 Planning, Acting, and Learning 
11 Alternative Search Formulations and Applications 
12 Adversarial Search 
13 The Propositional Calculus 
14 Resolution in The Propositional Calculus 
15 The Predicate Calculus 
16 Resolution in the Predicate Calculus 
17 Knowledge-Based Systems 
18 Representing Commonsense Knowledge 
19 Reasoning with Uncertain Information 
20 Learning and Acting with Bayes Nets 
21 The Situation Calculus 
22 Planning 
23 Multiple Agents 
24 Communication Among Agents 
25 Agent Architectures

/pdf/artificial-intelligence-a-new-synthesis-1mm7uhqtx9.pdf

Artificial Intelligence: A New Synthesis

Internet of Things (IoT) brings more than an explosive proliferation of endpoints. It is disruptive in several ways. In this chapter we examine those disruptions, and propose a hierarchical distributed architecture that extends from the edge of the network to the core nicknamed Fog Computing. In particular, we pay attention to a new dimension that IoT adds to Big Data and Analytics: a massively distributed number of sources at the edge.

Fog Computing: A Platform for Internet of Things and Analytics

An advanced method of tracking the three-dimensional motion of bodies has been developed. This system has the potential of dynamically characterizing robot motion and facilitating their end-point control. Three rotating planes of laser light, fixed and moving photovoltaic diode targets, and a pipe-lined architecture of analog and digital electronics are used to locate multiple targets whose number is only limited by available computer memory. Data collection rates are a function of the laser scan rotation speed and are currently selectable up to 480 hz. The tested performance on a preliminary prototype designed for 0.1 in accuracy (for tracking human motion) at a 480 hz data rate includes a resolution of 0.8 mm (0.03 inches), a repeatability of ± 0.635mm (± 0.025 inches), and an absolute accuracy of ± 2.0mm (± 0.08 inches) within an eight cubic meter volume with all results applicable at the 95% level of confidence along each coordinate direction. The system can be used to reduce XYZ target position data to body angular orientation for this first prototype ranges from ± 0.5 to ± 1 degree. Moving targets can be tracked at speeds exceeding 1 m/s with signal integrity tested but not limited to 25 hz motions.

Performance of the minnesota scanner: A prototype for 3-D tracking of moving body segments

Investigating the Effectiveness of Using Bluetooth Low-Energy Technology to Trigger In-Vehicle Messages in Work Zones

The viability of a delayed adaptive inverse method for motion control of the tip of a flexible beam is demonstrated in this paper. This method is based on an adaptive linear FIR filter which provides a stable and close approximation to the inverse plant dynamics. Such FIR filters can be used to control non-minimum phase systems, certain nonlinear systems, or plants of unknown dynamics and can be implemented using real-time interrupt driven high performance computational devices such as digital signal processing (DSP) based hardware. The effects of varying parameters of the delayed adaptive inverse controller (such as the values of the initial weights, the gain constants, and the length of delay) on the system performance are presented. Since the method is computationally efficient, it can be used in high bandwidth applications for control of complex plants given only the desired and the actual measured outputs for the plant. A feedback controller is used in conjunction with the delayed adaptive inverse controller to eliminate the residual errors that would occur if only feedforward control were used. This delayed adaptive inverse method is then compared to an H ? -based loopshaping controller.

Max Donath

Papers

Performance of the minnesota scanner: A prototype for 3-D tracking of moving body segments

Investigating the Effectiveness of Using Bluetooth Low-Energy Technology to Trigger In-Vehicle Messages in Work Zones

Non-Collocated Flexible Beam Motion Control based on a Delayed Adaptive Inverse Method

Optical considerations for in-process surface roughness sensing and control.

Development of a Freeway Queue Detection and Warning System using Ad-hoc Control and DSRC based V2V Communication