Adaptive model for a software test to calculate a residual error forecast

Computing ◽  
1989 ◽  
Vol 42 (2-3) ◽  
pp. 141-158
Author(s):  
P. Wildenauer ◽  
L. Eisner
2004 ◽  
pp. 4-34 ◽  
Author(s):  
E. Yasin ◽  
A. Yakovlev

Having analyzed the present state of the Russian economy the authors come to the conclusion that the only reasonable goal of its modernization is achieving high competitive capacity of production. External and internal competitive capacity is analysed in detail basing on broad statistics as well as competitive capacity of institutions and their changes, the adaptive model of transition economy. According to the authors implementation of competitive capacity policy as a national idea should take into account long-term perspective.


1997 ◽  
Author(s):  
Don McAndrews ◽  
Janice M. Ryan ◽  
Priscilla Fowler

Author(s):  
Xixin Wu ◽  
Yuewen Cao ◽  
Mu Wang ◽  
Songxiang Liu ◽  
Shiyin Kang ◽  
...  

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402098885
Author(s):  
Kuan-Jui Huang ◽  
Kuo-Huie Chiang

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.


2021 ◽  
Vol 11 (11) ◽  
pp. 5067
Author(s):  
Paulo Veloso Gomes ◽  
António Marques ◽  
João Donga ◽  
Catarina Sá ◽  
António Correia ◽  
...  

The interactivity of an immersive environment comes up from the relationship that is established between the user and the system. This relationship results in a set of data exchanges between human and technological actors. The real-time biofeedback devices allow to collect in real time the biodata generated by the user during the exhibition. The analysis, processing and conversion of these biodata into multimodal data allows to relate the stimuli with the emotions they trigger. This work describes an adaptive model for biofeedback data flows management used in the design of interactive immersive systems. The use of an affective algorithm allows to identify the types of emotions felt by the user and the respective intensities. The mapping between stimuli and emotions creates a set of biodata that can be used as elements of interaction that will readjust the stimuli generated by the system. The real-time interaction generated by the evolution of the user’s emotional state and the stimuli generated by the system allows him to adapt attitudes and behaviors to the situations he faces.


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