An Approach for Dynamic Evolution of Component-based Software

2010 ◽  
Author(s):  
Wang Wei ◽  
Li Tong
Keyword(s):  
Dynamic Evolution

Dynamic Evolution of Processes in Process-Aware Information Systems

2011 ◽  
Vol 22 (3) ◽  
pp. 417-438 ◽  
Author(s):  
Wei SONG ◽  
Xiao-Xing MA ◽  
Hao HU ◽  
Jian LÜ
Keyword(s):  
Information Systems ◽  
Dynamic Evolution

Dynamic evolution of shear rate-dependent behavior of rock discontinuity under shearing condition

2021 ◽  
Vol 28 (6) ◽  
pp. 1875-1887
Author(s):  
Lin-lin Gu ◽  
Zhen Wang ◽  
Feng Zhang ◽  
Fei Gao ◽  
Xiao Wang
Keyword(s):  
Shear Rate ◽  
Dynamic Evolution ◽  
Rock Discontinuity ◽  
Rate Dependent ◽  
Dependent Behavior

scholarly journals The Deterministic Evolution Of Illicit Drug Consumption Within a Given Population

2018 ◽  
Vol 62 ◽  
pp. 139-157 ◽  
Author(s):  
Yusra Bibi Ruhomally ◽  
Nabeelah Banon Jahmeerbaccus ◽  
Muhammad Zaid Dauhoo
Keyword(s):  
Drug Users ◽  
Illicit Drug ◽  
Drug Consumption ◽  
Dynamic Evolution ◽  
Evidence Based ◽  
Relative Importance ◽  
Epidemic Threshold ◽  
Drug Usage ◽  
Policy Makers ◽  
Reproduction Numbers

We study the NERA model that describes the dynamic evolution of illicit drug usage in a population. The model consists of nonusers (N) and three categories of drug users: the experimental (E) category, the recreational (R) category and the addict (A) category. Two epidemic threshold term known as the reproduction numbers, R0 and μ are defined and derived. Sensitivity analysis of R0 on the parameters are performed in order to determine their relative importance to illicit drug prevalence. The local and global stability of the equilibrium states are also analysed. We also prove that a transcritical bifurcation occurs at R0 = 1. It is shown that an effective campaign of prevention can help to fight against the prevalence of illicit drug consumption. We demonstrate persistence when R0 > 1 and conditions for the extinction of drug consumption are also established. Numerical simulations are performed to verify our model. Our results show that the NERA model can assist policy makers in targeting prevention for maximum effectiveness and can be used to adopt evidence-based policies to better monitor and quantify drug use trends.

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