Abstract: This research integrates systemic and participatory techniques to model the Russian Federation construction innovation system. Understanding this complex construction innovation system and determining the best levers for enhancing it require the dynamic modelling of a number of factors, such as flows of resources and activities, policies, uncertainty and time. To build the foundations for such a dynamic model, the employed study method utilised an integrated stakeholder-based participatory approach coupled with structural analysis (MICMAC—Matrice d'Impacts Croisés Multiplication Appliquée à un Classement Cross-Impact Matrix). This method identified the key factors of the Russian Federation construction innovation system, their causal relationship (i.e., influence/dependence map) and, ultimately, a causal loop diagram. The generated model reveals pathways to improving construction innovation in the Russian Federation and underpins the future development of an operationalised system dynamics model.
Abstract: Qualitative data is an important source of information for system dynamics modeling. It can potentially support any stage of the modeling process, yet it is mainly used in the early steps such as problem identification and model conceptualization. Existing approaches that outline a systematic use of qualitative data in model conceptualization are often not adopted for reasons of time constraints resulting from an abundance of data. In this paper, we introduce an approach that synthesizes the strengths of existing methods. This alternative approach (i) is focused on causal relationships starting from the initial steps of coding; (ii) generates a generalized and simplified causal map without recording individual relationships so that time consumption can be reduced; and (iii) maintains the links from the final causal map to the data sources by using software. We demonstrate an application of this approach in a study about integrated decision making in the housing sector of the UK.
Abstract: Complex systems are composed of a large number of individual components. Many of these systems are separable, i.e., they can be split into two coupled subsystems: one with foreground components and another with background components. The former leads to narrow peaks in the frequency spectrum of the system and the latter gives the broad-band part. There is coupling between the two subsystems, but they can be studied separately for purposes of modeling and for analysis of experimental data. Examples from the literature are given from the area of mechanical vibrations, but the approach is quite general and can be adapted to other kinds of problems.
Abstract: After having outlined the essential differences between non-complex systems and complex systems we briefly recall the conceptual approaches considered by the pre-complexity General Systems Theory introduced by Von Bertalanffy in 1968 and those of the science of complexity and post-Bertalanffy General Systems Theory. In this context, after outlining the concept of completeness, we consider cases of incompleteness in various disciplines to arrive at theoretical incompleteness. The latter is clarified through several cases of different natures and by approaches in the literature, such as logical openness, the Dynamic Usage of Models (DYSAM), and the principle of uncertainty in physics. The treatment and the contrast between completeness and incompleteness are introduced as a conceptual and cultural context, as knowledge to manage the knowledge society in analogy, for example, with the transition from the logic of certainty to that of uncertainty introduced by De Finetti. The conceptual framework of completeness is not appropriate for dealing with complexity. Conversely, the conceptual framework of incompleteness is consistent and appropriate with interdisciplinary complexity.
Abstract: Chaotic dynamics are an interesting topic in nonlinear science that has been intensively studied during the last three decades due to its wide availability. Motivated by much researches on synchronization, the authors of this study have improved the time response of stabilization when parametrically excited Φ6—Van der Pol Oscillator (VDPO) and Φ6—Duffing Oscillator (DO) are synchronized identically as well as non-identically (with each other) using the Linear Active Control (LAC) technique using Mathematica. Furthermore, the authors have synchronized the same pairs of the oscillators using a more robust synchronization with faster time response of stability called Robust Adaptive Sliding Mode Control (RASMC). A comparative study has been done between the previous results of Njah’s work and our results based on Mathematica via LAC. The time response of stabilization of synchronization using RASMC has been discussed.
Abstract: Dynamic sophisticated real-time adaptation is not possible with current e-learning technologies. Our proposal is based on changing the approach for the development of e-learning systems using dynamic languages and including them in both platforms and learning content specifications thereby making them adaptive. We propose a Sharable Auto-Adaptive Learning Object (SALO), defined as an object that includes learning content and describes its own behaviour supported by dynamic languages. We describe an example implementation of SALO for the delivery and assessment of a web development course using Moodle rubrics. As a result, the learning objects can dynamically adapt their characteristics and behaviour in e-learning platforms.