Time-dependent spectral analysis and its application in prediction and control

1971 ◽  
Vol 17 (4) ◽  
pp. 517-534 ◽  
Author(s):  
M.B. Priestley
Keyword(s):  
Spectral Analysis ◽  
Time Dependent ◽  
Prediction And Control ◽  
And Control

scholarly journals Degenerate time-dependent network dynamics anticipate seizures in human epileptic brain

2016 ◽  
Author(s):  
Adrià Tauste Campo ◽  
Alessandro Principe ◽  
Miguel Ley ◽  
Rodrigo Rocamora ◽  
Gustavo Deco
Keyword(s):  
Epileptic Seizures ◽  
Time Dependent ◽  
Clear Understanding ◽  
Intracranial Eeg ◽  
Critical Phase ◽  
Prediction And Control ◽  
Eeg Recordings ◽  
Highly Correlated ◽  
Network States ◽  
And Control

AbstractEpileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide cross-validated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial EEG recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable (“degenerate”) and is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to particularly affect the activity of resection regions in patients with validated postsurgical outcome. Our approach characterizes pre-seizure networks dynamics as a cascade of two sequential events providing new insights into seizure 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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