Self-adaptive model-based online testing for dynamic SOA

2017 ◽  
Author(s):  
Lucas Carvalho Leal
Keyword(s):  
Online Testing ◽  
Adaptive Model ◽  
Model Based ◽  
Self Adaptive

Self-adaptive model-based ECG denoising using features extracted by mean shift algorithm

2010 ◽  
Vol 5 (2) ◽  
pp. 103-113 ◽  
Author(s):  
Jingyu Yan ◽  
Yan Lu ◽  
Jia Liu ◽  
Xinyu Wu ◽  
Yangsheng Xu
Keyword(s):  
Mean Shift ◽  
Adaptive Model ◽  
Mean Shift Algorithm ◽  
Model Based ◽  
Ecg Denoising ◽  
Self Adaptive

scholarly journals A Self-Adaptive Model-Based Wi-Fi Indoor Localization Method

Sensors ◽  
2016 ◽  
Vol 16 (12) ◽  
pp. 2074 ◽  
Author(s):  
Jure Tuta ◽  
Matjaz Juric
Keyword(s):  
Indoor Localization ◽  
Adaptive Model ◽  
Localization Method ◽  
Model Based ◽  
Self Adaptive

scholarly journals Toward a Self-Adaptive Cyberdefense Framework in Organization

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402098885
Author(s):  
Kuan-Jui Huang ◽  
Kuo-Huie Chiang
Keyword(s):  
Information System ◽  
Organizational Learning ◽  
Intelligent Agents ◽  
Coordination Mechanism ◽  
Learning Effects ◽  
Adaptive Model ◽  
Dynamic Propagation ◽  
The Future ◽  
Adaptive Framework ◽  
Self Adaptive

Organizations suffer more than ever from the inability to securely manage the information system, despite their myriad efforts. By introducing a real cyberattack of a bank, this research analyzes the characteristics of modern cyberattacks and simulates the dynamic propagation that makes them difficult to manage. It develops a self-adaptive framework that through simulation, distinctly improves cyberdefense efficiency. The results illustrate the discrepancies of the previous studies and validate the use of a time-based self-adaptive model for cybersecurity management. The results further show the significance of human and organizational learning effects and a coordination mechanism in obtaining a highly dependable cyberdefense setting. This study also provides an illuminating analysis for humans to position themselves in the collaborations with increasingly intelligent agents in the future.

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