David Wang

Bio: David Wang is an academic researcher from University of Minnesota. The author has contributed to research in topics: Adaptive control & Inverse problem. The author has an hindex of 3, co-authored 6 publications receiving 1604 citations.

Exercised-induced vasovagal syncope: Limiting the risks

Abstract: Syncopal episodes in an athlete require a thorough evaluation because some of the possible causes are life-threatening. Two case studies demonstrate the diagnostic work-up, which typically involves electrocardiography, echocardiography, and exercise testing. Tilt-table testing can be used to confirm a diagnosis of vasovagal syncope, but only after structural heart disease has been ruled out. Treatment of vasovagal syncope includes avoiding dehydration and using one or a combination of medications shown to be useful for this condition. Care must be exercised in choosing medications; some are prohibited in organized athletics, and some can hurt performance.

Spondylolysis Incidence in Various Sports

Abstract: ‘Best of the Literature’ presents summaries of sports medicine—related articles culled from more than 30 medical journals. Experts comment on what the new findings add to current medical thinking and on the implications for practice.

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

Abstract: 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.

Turbulence, Coherent Structures, Dynamical Systems and Symmetry

Abstract: 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.

Fog Computing: A Platform for Internet of Things and Analytics

Abstract: 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.

Recent Research in Cooperative Control of Multivehicle Systems

Abstract: This paper presents a survey of recent research in cooperative control of multivehicle systems, using a common mathematical framework to allow different methods to be described in a unified way. The survey has three primary parts: an overview of current applications of cooperative control, a summary of some of the key technical approaches that have been explored, and a description of some possible future directions for research. Specific technical areas that are discussed include formation control, cooperative tasking, spatiotemporal planning, and consensus.

A survey on motion prediction and risk assessment for intelligent vehicles

Abstract: With the objective to improve road safety, the automotive industry is moving toward more “intelligent” vehicles. One of the major challenges is to detect dangerous situations and react accordingly in order to avoid or mitigate accidents. This requires predicting the likely evolution of the current traffic situation, and assessing how dangerous that future situation might be. This paper is a survey of existing methods for motion prediction and risk assessment for intelligent vehicles. The proposed classification is based on the semantics used to define motion and risk. We point out the tradeoff between model completeness and real-time constraints, and the fact that the choice of a risk assessment method is influenced by the selected motion model.

Cuckoo Optimization Algorithm

Abstract: In this paper a novel evolutionary algorithm, suitable for continuous nonlinear optimization problems, is introduced. This optimization algorithm is inspired by the life of a bird family, called Cuckoo. Special lifestyle of these birds and their characteristics in egg laying and breeding has been the basic motivation for development of this new evolutionary optimization algorithm. Similar to other evolutionary methods, Cuckoo Optimization Algorithm (COA) starts with an initial population. The cuckoo population, in different societies, is in two types: mature cuckoos and eggs. The effort to survive among cuckoos constitutes the basis of Cuckoo Optimization Algorithm. During the survival competition some of the cuckoos or their eggs, demise. The survived cuckoo societies immigrate to a better environment and start reproducing and laying eggs. Cuckoos' survival effort hopefully converges to a state that there is only one cuckoo society, all with the same profit values. Application of the proposed algorithm to some benchmark functions and a real problem has proven its capability to deal with difficult optimization problems.