Stochastic Linearization by Data Dependent Systems

1977 ◽  
Vol 99 (4) ◽  
pp. 221-226 ◽  
Author(s):  
S. M. Pandit
Keyword(s):  
Furnace Operation ◽  
System Response ◽  
Ticket Sales ◽  
Response Data ◽  
Machine Tool Chatter ◽  
Chatter Vibrations ◽  
Stochastic Linearization ◽  
Airline Passenger ◽  
Prediction And Control ◽  
And Control

The paper presents and illustrates a method of stochastic linearization of nonlinear systems. The system response to white noise excitation is modeled by a differential equation, which provides the necessary transfer function. The linearization is optimal in the mean squared sense within the statistical limits imposed by the response. Since the linearization is accomplished purely from the response data, governing equations of the system need not be known. An application to machine tool chatter vibrations illustrates stability assessment and modal analysis. The ease with which optimal prediction and control equations can be derived and implemented is shown by an application to blast furnace operation. Detection and verification of limit cycles are illustrated by a model for airline passenger ticket sales data.

scholarly journals Damping Measurements Using Operational Data

1996 ◽  
Vol 118 (3) ◽  
pp. 190-193 ◽  
Author(s):  
G. H. James ◽  
T. G. Carne ◽  
P. S. Veers
Keyword(s):  
Wind Turbine ◽  
Strain Gauge ◽  
Test Bed ◽  
Data Set ◽  
Response Data ◽  
Modal Damping ◽  
Gauge Data ◽  
Prediction And Control ◽  
And Control ◽  
Operational Data

We have measured modal damping using strain-gauge data from an operating wind turbine. This new technique for measuring modal damping is easier and less expensive than previously used methods. Auto-correlation and cross-correlation functions of the strain-gauge data have been shown to consist of decaying sinusoids which correspond to the modal frequencies and damping ratios of the wind turbine. We have verified the method by extracting damping values from an analytically generated data set. Actual operating response data from the DOE/Sandia 34-m Test Bed has been used to calculate modal damping ratios as a function of rotor rotation rate. This capability will allow more accurate fatigue life prediction and control.

An insight into Case Management and Challenges in Veteran Suicide Prevention

2020 ◽  
pp. 14-25
Author(s):  
Tamara Green
Keyword(s):  
Case Management ◽  
Suicide Prevention ◽  
Suicide Risk ◽  
Digital Transformation ◽  
Prevention Science ◽  
Historical Records ◽  
Military Members ◽  
Prediction And Control ◽  
And Control ◽  
Insight Into

Much of the literature, policies, programs, and investment has been made on mental health, case management, and suicide prevention of veterans. The Australian “veteran community is facing a suicide epidemic for the reasons that are extremely complex and beyond the scope of those currently dealing with them.” (Menz, D: 2019). Only limited work has considered the digital transformation of loosely and manual-based historical records and no enablement of Artificial Intelligence (A.I) and machine learning to suicide risk prediction and control for serving military members and veterans to date. This paper presents issues and challenges in suicide prevention and management of veterans, from the standing of policymakers to stakeholders, campaigners of veteran suicide prevention, science and big data, and an opportunity for the digital transformation of case management.

A case study of wear-type rail corrugation prediction and control using speed variation

2009 ◽  
Vol 325 (1-2) ◽  
pp. 85-105 ◽  
Author(s):  
P.A. Meehan ◽  
P.A. Bellette ◽  
R.D. Batten ◽  
W.J.T. Daniel ◽  
R.J. Horwood
Keyword(s):  
Rail Corrugation ◽  
Speed Variation ◽  
Prediction And Control ◽  
And Control

Phenomenological Foundations for the Study of Suicide

1973 ◽  
Vol 4 (3) ◽  
pp. 195-208
Author(s):  
Keith Hoeller
Keyword(s):  
Great Emphasis ◽  
Prediction And Control ◽  
And Control

Is death the “enemy” to be avoided at all costs or is it to be faced, engendering liberation and rebirth? Contemporary suicidology concerns itself with the “causes” of suicide, placing great emphasis on prediction and control However, when the “meaning” of suicide is studied, understanding it as a human phenomenon becomes of major concern. Part of this understanding requires one to view “dread” as implying the possibility of making one's existence one's own, rather than something that must be prevented. In the study of suicide, revolutionary insights can emerge if less emphasis is placed on death as the “enemy” and more attention is placed on “dread” as a potential liberator.

scholarly journals Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 492
Author(s):  
Valentina Y. Guleva ◽  
Polina O. Andreeva ◽  
Danila A. Vaganov
Keyword(s):  
Social Networks ◽  
Sampling Method ◽  
Building Blocks ◽  
Global Dynamics ◽  
Diffusion Dynamics ◽  
Different Types ◽  
Prediction And Control ◽  
Path Lengths ◽  
And Control ◽  
Diffusion Prediction

Finding the building blocks of real-world networks contributes to the understanding of their formation process and related dynamical processes, which is related to prediction and control tasks. We explore different types of social networks, demonstrating high structural variability, and aim to extract and see their minimal building blocks, which are able to reproduce supergraph structural and dynamical properties, so as to be appropriate for diffusion prediction for the whole graph on the base of its small subgraph. For this purpose, we determine topological and functional formal criteria and explore sampling techniques. Using the method that provides the best correspondence to both criteria, we explore the building blocks of interest networks. The best sampling method allows one to extract subgraphs of optimal 30 nodes, which reproduce path lengths, clustering, and degree particularities of an initial graph. The extracted subgraphs are different for the considered interest networks, and provide interesting material for the global dynamics exploration on the mesoscale base.

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