Shrinkage of Cured Fluoroelastomers. II. Shrinkage Control

1976 ◽  
Vol 49 (1) ◽  
pp. 43-51 ◽  
Author(s):  
J. D. MacLachlan ◽  
A. W. Fogiel
Keyword(s):  
Bituminous Coal ◽  
Practical Applications ◽  
Weight Losses ◽  
Elastomeric Matrix ◽  
The Press ◽  
Prediction And Control ◽  
And Control ◽  
Preparation Techniques ◽  
Diameter Shrinkage ◽  
Volatile Materials

Abstract Processing variables have been examined for the prediction and control of mold shrinkage in directions pertinent to practical applications. (1) Of the total shrinkage of finished parts, more than 75% results from the press cure, and the remainder is the result of weight losses during the subsequent oven cure. (2) Mold shrinkage may be reduced by addition of CaO, bituminous coal fines, or epoxy resins. Shrinkage can be increased by addition of volatile materials. (3) Control of shrinkage may also be effected with acicular fillers or filler mixtures through fiber orientation in the elastomeric matrix in the desired direction. In the case of O-rings, inside diameter shrinkage values ranging from zero to three per cent can be produced in a controllable manner by blank preparation techniques commonly used in the industry.

Intelligent Control and Optimal Operation of Complex Electric Power Systems Using Hierarchical Neural Networks

2010 ◽  
pp. 291-320
Author(s):  
Dingguo Chen ◽  
Ronald R. Mohler
Keyword(s):  
Neural Networks ◽  
Power Systems ◽  
Optimal Operation ◽  
System Stability ◽  
Practical Applications ◽  
Control Robustness ◽  
Optimization And Control ◽  
Prediction And Control ◽  
Hierarchical Neural Networks ◽  
And Control

This chapter is aimed at developing a unified neural network based framework that can be utilized in prediction and control of complex dynamic system behaviors. In particular, in power systems, accurate prediction of system load behavior provides vital information to allow for optimal planning and most economic operation of power systems; on the other hand, the real-time system stability must be maintained against various random factors, disturbances and contingencies. The hierarchical neural networks are studied in depth in the context of prediction, optimization and control; and unified design techniques are developed for providing control robustness, optimality and prediction accuracy as well. The unified methodology builds upon hierarchical neural networks, and may be utilized and extended for other practical applications.

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.

Animal Pain Scales in Public Policy

1990 ◽  
Vol 18 (1_part_1) ◽  
pp. 41-50
Author(s):  
F. Barbara Orlans
Keyword(s):  
Public Policy ◽  
Animal Welfare ◽  
The United States ◽  
Pain Scale ◽  
Laboratory Animals ◽  
Practical Applications ◽  
Animal Pain ◽  
Pain Scales ◽  
History Of ◽  
And Control

Pain scales classify the severity of pain inflicted on laboratory animals from little or none up to severe. A pain scale as part of public policy serves beneficial purposes that promote animal welfare. It can be used to educate people about the two alternatives of refinement and replacement, and the need to reduce animal pain. Furthermore, a pain scale has practical applications: 1) in review procedures for animal welfare concerns; 2) in developing policies on the use of animals in education; and 3) as a basis for collecting national data on animal experimentation, so that meaningful data can be collected on trends in reduction and control in animal pain. So far, only a few countries (including Sweden, the Netherlands, Canada and New Zealand) have adopted pain scales as part of their public policy. Most countries, including the United States, have not yet done so. The history of the development and adoption of pain scales by various countries is described and the case is presented for wider adoption of a pain scale in countries not currently using one.

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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