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Managing a Conflict Environment of Digitalization
Published in Sergey V. Samoilenko, Digitalization, 2023
We can summarize the basic characteristics of complex non-linear dynamic systems as follows: A system is complex if it consists of a large number of interacting components.The interactions between the components of a complex system are associated with the presence of a feedback mechanism, which, due to the non-linearity of the feedback-controlled interactions, makes a complex system itself non-linear and causes it to exhibit/develop emergent properties (e.g., appearance of independently observable and empirically verifiable patterns of the collective behavior of the system).Complex system is dynamic if its state or behavior changes with time.Complex system is deterministic in terms of the cause and effect, if the variables describing it relate to each other in a non-probabilistic way.
Resilience Engineering in Prehospital Emergency Medical Services
Published in Joseph R. Keebler, Elizabeth H. Lazzara, Paul Misasi, Human Factors and Ergonomics of Prehospital Emergency Care, 2017
Shawn Pruchnicki, Sidney Dekker
Regardless of the cause of a system-wide decompensation and possible failure, there are inherent characteristics to the patterns experienced. Typically, as designed, complex systems frequently experience perturbations (normative) and the designed adaptive capacities and resilience abilities prevent failure. This is what we plan for, as these are challenges that we have seen before and also expect in the future. Examples might include second alarms calling for additional personnel or heavy equipment brought to the scene to manage an extrication that is now more clearly understood to be more difficult than first appreciated. These adaptations that are constructed under time pressure are the hallmark of a system that is designed to operate in a complex dynamic environment. Typically, most operations in the prehospital EMS recognize these challenges and provide both training and procedures to match when recognized by on-scene personnel.
Intelligent Cloud
Published in Haishi Bai, Zen of Cloud, 2019
A complex system is a system that is made up of many interacting components. A complex system is different from a complicated system. A complicated system can often be decomposed and studied piece-by-piece. For example, a car is a complicated system. You can decompose a car into smaller components, understand how each component works, and then infer how a complete car works. The complexity of a complex system resides in the interactive dynamics of the components. When you isolate the components, a complex system collapses.
Mitigating ripple effect in supply networks: the effect of trust and topology on resilience
Published in International Journal of Production Research, 2022
Ilaria Giannoccaro, Anas Iftikhar
To date, there is no consensus on the definition of supply network resilience (Hohenstein et al. 2015; Kim, Chen, and Linderman 2015). Researchers either adopt definitions as per the scope of their research or develop their own definition considering their research aim. Furthermore, some scholars define supply chain resilience referring to a single dimension (Brandon-Jones et al. 2014; Ambulkar, Blackhurst, and Grawe 2015; Gölgeci and Ponomarov 2015; Liu and Lee 2018), while others prefer multi-dimensional definitions (Zsidisin and Wagner 2010). These dimensions mainly include robustness, flexibility, agility, and adaptability. In such a view, resilience is a multi-faceted capability of complex systems that encompasses avoiding, absorbing, adapting to and recovering from disruptions.
Stochastic pretopology as a tool for complex networks analysis
Published in Journal of Information and Telecommunication, 2019
Quang Vu Bui, Soufian Ben Amor, Marc Bui
Complex system is a system composed of many interacting parts, such that the collective behaviour of its parts together is more than the ‘sum’ of their individual behaviours (Newman, 2011). The topology of complex systems (who interact with whom) is often specified in terms of complex networks that are usually modelled by graphs, composed by vertices or nodes and edges or links. Graph theory has been widely used in the conceptual framework of network models, such as random graphs, small world networks, scale-free networks (Easley & Kleinberg, 2010; Newman, 2003).