Дисертації: "Complex adaptive systems (CAS)"

1

Leduc, Nathaniel. "Understanding Collaboration in the Context of Loosely- and Tightly-Coupled Complex Adaptive Systems." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37087.

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Many of the technological and social systems our society has come to depend on can be classified as complex adaptive systems (CAS). These systems are made of many individual parts that self-organize to respond and adapt to changing outside and inside influences affecting the system and its actors. These CAS can be placed on a spectrum ranging from loosely- to tightly-coupled, depending on the degree of interrelatedness and interdependence between system components. This research has explored how the process of collaboration occurs in both a loosely- and tightly-coupled setting using one exemplar of each system. The loosely-coupled exemplar related to disaster risk reduction in two Canadian communities while the tightly-coupled one involved the implementation of a surgical information management system in a Canadian hospital. A list of core elements of collaboration that should be considered essential to the success of all collaborative endeavours was developed as a result: Engagement, Communication, Leadership, Role Clarity, Awareness, Time, and Technical Skills and Knowledge. Based on observing how the core elements of collaboration interacted with one another within each of these example systems, two models were created to represent their relationships. A list of considerations that collaborative tool designers should consider was also developed and the implications of these considerations were discussed. As businesses and other organizations increasingly incorporate team-based work models, they will come to depend more heavily on technology-based solutions to support collaboration. By incorporating collaborative technologies that properly support the activity of these teams—based on the specific type of complex adaptive system in which their organization exists—organizations can avoid wasting time and resources developing tools that hinder collaboration.

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2

Fredericks, Jeanne. "Towards an understanding of the boundaries and characteristics of a Digital Business Strategy." Doctoral thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/32673.

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The merging of business and information technology (IT) strategies, effectively becoming a Digital Business Strategy (DBS), is changing the way that organisations have to leverage resources to create differential value. Due to the DBS being such a novice idea, there is no clear understanding of what the DBS is, what its characteristics and boundaries are, how it impacts alignment between business and IT, and how it impacts organisational performance. Without this understanding, organisations leveraging a DBS run the risk of launching technological initiatives or making organisational changes that are disjointed from their strategic direction. These misaligned efforts may result in unrealised strategy and unsatisfactory organisational performance. The purpose of this study was to define the boundaries and characteristics of the DBS, provide a definition of a DBS and to establish if the DBS has a positive effect on organisational performance. To examine the DBS, it was observed in its natural habitat, through a single case study approach, focusing on an organisation that has been leveraging a DBS as part of their digital journey. The organisation is a South African based financial services provider and is a subsidiary of a larger financial services provider. In this study, the DBS was observed from an intellectual, operational, social and cultural alignment perspective, using a combination of the Strategic Alignment Model (SAM) and the Complex Adaptive System (CAS) frameworks. This study subscribed to a mixed-method approach which included both qualitative and quantitative research techniques. Staff providing input into this study included senior, middle, junior and non-management employees. The study was conducted over a period of thirteen months. The findings from both the qualitative and quantitative data suggest that to leverage a DBS the organisation must be concerned with more than just leveraging digital resources. For instance, organisations must focus on customer and staff empowerment, use customer and industry-related information to create opportunistic and competitive decision-making opportunities, and create a change-ready culture where bold experimentation and failing forward is embraced. Researchers and practitioners alike can use the findings of this case study as lessons on how to leverage organisational resources in the context of the DBS.

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3

Bondorowicz, Stefan. "Adaptive control of complex dynamic systems." Thesis, University of Oxford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302787.

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4

Yang, Ang Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "A networked multi-agent combat model : emergence explained." Awarded by:University of New South Wales - Australian Defence Force Academy. School of Information Technology and Electrical Engineering, 2007. http://handle.unsw.edu.au/1959.4/38823.

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Simulation has been used to model combat for a long time. Recently, it has been accepted that combat is a complex adaptive system (CAS). Multi-agent systems (MAS) are also considered as a powerful modelling and development environment to simulate combat. Agent-based distillations (ABD) - proposed by the US Marine Corp - are a type of MAS used mainly by the military for exploring large scenario spaces. ABDs that facilitated the analysis and understanding of combat include: ISAAC, EINSTein, MANA, CROCADILE and BactoWars. With new concepts such as networked forces, previous ABDs can implicitly simulate a networked force. However, the architectures of these systems limit the potential advantages gained from the use of networks. In this thesis, a novel network centric multi-agent architecture (NCMAA) is pro-posed, based purely on network theory and CAS. In NCMAA, each relationship and interaction is modelled as a network, with the entities or agents as the nodes. NCMAA offers the following advantages: 1. An explicit model of interactions/relationships: it facilitates the analysis of the role of interactions/relationships in simulations; 2. A mechanism to capture the interaction or influence between networks; 3. A formal real-time reasoning framework at the network level in ABDs: it interprets the emergent behaviours online. For a long time, it has been believed that it is hard in CAS to reason about emerging phenomena. In this thesis, I show that despite being almost impossible to reason about the behaviour of the system by looking at the components alone because of high nonlinearity, it is possible to reason about emerging phenomena by looking at the network level. This is undertaken through analysing network dynamics, where I provide an English-like reasoning log to explain the simulation. Two implementations of a new land-combat system called the Warfare Intelligent System for Dynamic Optimization of Missions (WISDOM) are presented. WISDOM-I is built based on the same principles as those in existing ABDs while WISDOM-II is built based on NCMAA. The unique features of WISDOM-II include: 1. A real-time network analysis toolbox: it captures patterns while interaction is evolving during the simulation; 2. Flexible C3 (command, control and communication) models; I 3. Integration of tactics with strategies: the tactical decisions are guided by the strategic planning; 4. A model of recovery: it allows users to study the role of recovery capability and resources; 5. Real-time visualization of all possible information: it allows users to intervene during the simulation to steer it differently in human-in-the-loop simulations. A comparison between the fitness landscapes of WISDOM-I and II reveals similarities and differences, which emphasise the importance and role of the networked architecture and the addition of strategic planning. Lastly but not least, WISDOM-II is used in an experiment with two setups, with and without strategic planning in different urban terrains. When the strategic planning was removed, conclusions were similar to traditional ABDs but were very different when the system ran with strategic planning. As such, I show that results obtained from traditional ABDs - where rational group planning is not considered - can be misleading. Finally, the thesis tests and demonstrates the role of communication in urban ter-rains. As future warfighting concepts tend to focus on asymmetric warfare in urban environments, it was vital to test the role of networked forces in these environments. I demonstrate that there is a phase transition in a number of situations where highly dense urban terrains may lead to similar outcomes as open terrains, while medium to light dense urban terrains have different dynamics

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5

Kingston, Kenneth Samuel. "Applications of complex adaptive systems approaches to coastal systems." Thesis, University of Plymouth, 2003. http://hdl.handle.net/10026.1/474.

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This thesis investigates the application of complex adaptive systems approaches (e.g. Artificial Neural Networks and Evolutionary Computation) to the study of coastal hydrodynamic and morphodynamic behaviour. Traditionally, nearshore morphological coastal system studies have developed an understanding of those physical processes occurring on both short temporal, and small spatial scales with a large degree of success. The associated approaches and concepts used to study the coastal system at these scales have primarily been linear in nature. However, when these approaches to studying the coastal system are extended to investigating larger temporal and spatial scales, which are commensurate with the aims of coastal management, results have had less success. The lack of success in developing an understanding of large scale coastal behaviour is to a large extent attributable to the complex behaviour associated with the coastal system. This complexity arises as a result of both the stochastic and chaotic nature of the coastal system. This allows small scale system understanding to be acquired but prevents the larger scale behaviour to be predicted effectively. This thesis presents four hydro-morphodynamic case studies to demonstrate the utility of complex adaptive system approaches for studying coastal systems. The first two demonstrate the application of Artificial Neural Networks, whilst the latter two illustrate the application of Evolutionary Computation. Case Study #1 considers the nature of the discrepancy between the observed location of wave breaking patterns over submerged sandbars and the actual sandbar locations. Artificial Neural Networks were able to quantitatively correct the observed locations to produce reliable estimates of the actual sand bar locations. Case Study #2 considers the development of an approach for the discrimination of shoreline location in video images for the production of intertidal maps of the nearshore region. In this case the system modelled by the Artificial Neural Network is the nature of the discrimination model carried out by the eye in delineating a shoreline feature between regions of sand and water. The Artificial Neural Network approach was shown to robustly recognise a range of shoreline features at a variety of beaches and hydrodynamic settings. Case Study #3 was the only purely hydrodynamic study considered in the thesis. It investigated the use of Evolutionary Computation to provide means of developing a parametric description of directional wave spectra in both reflective and nonreflective conditions. It is shown to provide a unifying approach which produces results which surpassed those achieved by traditional analysis approaches even though this may not strictly have been considered as a fiddly complex system. Case Study #4 is the most ambitious application and addresses the need for data reduction as a precursor when trying to study large scale morphodynamic data sets. It utilises Evolutionary Computation approaches to extract the significant morphodynamic variability evidenced in both directly and remotely sampled nearshore morphologies. Significant data reduction is achieved whilst reWning up to 90% of the original variability in the data sets. These case studies clearly demonstrate the ability of complex adaptive systems to be successfully applied to coastal system studies. This success has been shown to equal and sometimess surpass the results that may be obtained by traditional approaches. The strong performance of Complex Adaptive System approaches is closely linked to the level of complexity or non-linearity of the system being studied. Based on a qualitative evaluation, Evolutionary Computation was shown to demonstrate an advantage over Artificial Neural Networks in terms of the level of new insights which may be obtained. However, utility also needs to consider general ease of applicability and ease of implementation of the study approach. In this sense, Artificial Neural Networks demonstrate more utility for the study of coastal systems. The qualitative assessment approach used to evaluate the case studies in this thesis, may be used as a guide for choosing the appropriateness of either Artificial Neural Networks or Evolutionary Computation for future coastal system studies.

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Shenoy, Rajiv. "Overset adaptive strategies for complex rotating systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51796.

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The resolution of the complex physics of rotating configurations is critical for any engineering analysis that requires multiple frames of reference. Two well-known applications are in the rotorcraft and wind energy industries. Rotor wake impingement from rotor-fuselage and wind turbine-tower interactions impact structural and acoustic characteristics. Additionally, parasite drag resulting from rotorcraft hubs may result in severe limitations on forward flight vehicle performance. Complex turbulent wakes from rotors and hubs impinging on downstream empennage can create adverse aeroelastic behavior and can affect handling qualities. Numerical simulations of these flows require state-of-the-art Navier Stokes methods using dynamic overset grids. However, many current methods typically used in industry result in wakes that dissipate essential features. In order to address these concerns, two advancements are introduced in this thesis. Feature-based grid adaptation on dynamic overset grids has been developed and demonstrated with an unstructured Navier Stokes solver. The unique feature of the adaptation technique is that it is applied globally on the overset grid system except within the boundary layer. In concert with grid adaptation, an efficient parallelized search algorithm for solution interpolation over massively distributed systems has been created. This results in cost-effective interpolation that retains the numerical order of accuracy and has been verified in both space and time. The improvements have been demonstrated for rotor-fuselage interaction and a generic rotating hub. Detailed analysis of convergence of the methodology and sensitivity of the results to relevant parameters have also been included.

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Morris, Paul John. "Modelling peatlands as a complex adaptive systems." Thesis, Queen Mary, University of London, 2010. http://qmro.qmul.ac.uk/xmlui/handle/123456789/479.

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A new conceptual approach to modelling peatlands, DigiBog, involves a Complex Adaptive Systems consideration of raised bogs. A new computer hydrological model is presented, tested, and its capabilities in simulating hydrological behaviour in a real bog demonstrated. The hydrological model, while effective as a stand-alone modelling tool, provides a conceptual and algorithmic structure for ecohydrological models presented later. Using DigiBog architecture to build a cellular model of peatland patterning dynamics, various rulesets were experimented with to assess their effectiveness in predicting patterns. Contrary to findings by previous authors, the ponding model did not predict patterns under steady hydrological conditions. None of the rulesets presented offered an improvement over the existing nutrient-scarcity model. Sixteen shallow peat cores from a Swedish raised bog were analysed to investigate the relationship between cumulative peat decomposition and hydraulic conductivity, a relationship previously neglected in models of peatland patterning and peat accumulation. A multivariate analysis showed depth to be a stronger control on hydraulic conductivity than cumulative decomposition, reflecting the role of compression in closing pore spaces. The data proved to be largely unsuitable for parameterising models of peatland dynamics, due mainly to problems in core selection. However, the work showed that hydraulic conductivity could be expressed quantitatively as a function of other physical variables such as depth and cumulative decomposition. DigiBog architecture was used to build a simple, vertical, ecohydrological model of long-term peat accumulation. As model complexity was increased under a self-organisation approach, model predictions of peat accumulation rates and surface wetness changed dramatically, revealing the importance of feedbacks between peatland hydrological behaviour and peat physical properties. This work may have important implications for palaeoclimatic reconstructions which assume peatland surface wetness to be a reliable climatic indicator. The expansion of the model to include horizontal space altered model behaviour in quantitative and qualitative terms.

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8

Hammer, Roger Julius. "Strategy development process and complex adaptive systems." Thesis, Aston University, 2011. http://publications.aston.ac.uk/15812/.

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The two areas of theory upon which this research was based were 'strategy development process' (SDP) and 'complex adaptive systems' (CAS), as part of complexity theory, focused on human social organisations. The literature reviewed showed that there is a paucity of empirical work and theory in the overlap of the two areas, providing an opportunity for contributions to knowledge in each area of theory, and for practitioners. An inductive approach was adopted for this research, in an effort to discover new insights to the focus area of study. It was undertaken from within an interpretivist paradigm, and based on a novel conceptual framework. The organisationally intimate nature of the research topic, and the researcher's circumstances required a research design that was both in-depth and long term. The result was a single, exploratory, case study, which included use of data from 44 in-depth, semi-structured interviews, from 36 people, involving all the top management team members and significant other staff members; observations, rumour and grapevine (ORG) data; and archive data, over a 5½ year period (2005-2010). Findings confirm the validity of the conceptual framework, and that complex adaptive systems theory has potential to extend strategy development process theory. It has shown how and why the strategy process developed in the case study organisation by providing deeper insights to the behaviour of the people, their backgrounds, and interactions. Broad predictions of the 'latent strategy development' process and some elements of the strategy content are also possible. Based on this research, it is possible to extend the utility of the SDP model by including peoples' behavioural characteristics within the organisation, via complex adaptive systems theory. Further research is recommended to test limits of the application of the conceptual framework and improve its efficacy with more organisations across a variety of sectors.

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9

Kennedy, Cameron. "Mass media and media complex adaptive systems, towards a complex methodology." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0002/MQ43352.pdf.

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10

Kennedy, Cameron (Cameron John) Carleton University Dissertation Journalism and Communication. "Mass media and media complex adaptive systems; towards a complex methodology." Ottawa, 1999.

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11

Jefferies, Paul. "Emergent phenomena of complex adaptive systems : financial markets." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427625.

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12

Fonseca, Jose Manuel Lopes Da. "Innovation : a property of complex adaptive social systems." Thesis, University of Hertfordshire, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263031.

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13

Atkinson, Simon Reay. "Engineering design adaptation fitness in complex adaptive systems." Thesis, University of Cambridge, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.648674.

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14

Dougherty, Francis Laverne. "A Complex Adaptive Systems Analysis of Productive Efficiency." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/65146.

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Linkages between Complex Adaptive Systems (CAS) thinking and efficiency analysis remain in their infancy. This research associates the basic building blocks of the CAS 'flocking' metaphor with the essential building block concepts of Data Envelopment Analysis (DEA). Within a proposed framework DEA"decisionmaking units" (DMUs) are represented as agents in the agent-based modeling (ABM) paradigm. Guided by simple rules, agent DMUs representing business units of a larger management system, 'align' with one another to achieve mutual protection/risk reduction and 'cohere' with the most efficient DMUs among them to achieve the greatest possible efficiency in the least possible time. Analysis of the resulting patterns of behavior can provide policy insights that are both evidencebased and intuitive. This research introduces a consistent methodology that will be called here the Complex Adaptive Productive Efficiency Method (CAPEM) and employs it to bridge these domains. This research formalizes CAPEM mathematically and graphically. It then conducts experimentation employing using the resulting CAPEM simulation using data of a sample of electric power plants obtained from Rungsuriyawiboon and Stefanou (2003). Guided by rules, individual agent DMUs (power plants) representing business units of a larger management system,'align' with one another to achieve mutual protection/risk reduction and 'cohere' with the most efficient DMUs among them to achieve the greatest possible efficiency in the least possible time. Using a CAS ABM simulation, it is found that the flocking rules (alignment, cohesion and separation), taken individually and in selected combinations, increased the mean technical efficiency of the power plant population and conversely decreased the time to reach the frontier. It is found however that these effects were limited to a smaller than expected sub-set of these combinations of the flocking factors. Having been successful in finding even a limited sub-set of flocking rules that increased efficiency was sufficient to support the hypotheses and conclude that employing the flocking metaphor offers useful options to decision-makers for increasing the efficiency of management systems.
Ph. D.

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Engler, Joseph John. "Innovation as a complex adaptive system." Thesis, University of Iowa, 2009. https://ir.uiowa.edu/etd/233.

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Innovation has long been considered crucial for companies to gain a competitive edge in the global marketplace. Unfortunately, a solid understanding of the system of innovation does not exist. The literature lacks formal definitions and methodologies for the system of innovation. Many surrogates for innovation metrics have been posited in past research but none have solidified the overall concept of an innovation system or science. It has been speculated that innovation as a system is complex. Additionally, some researchers have suggested that this innovation system is adaptive. In these instances, of the literature, surrogates were again utilized in place of solid modeling and hypothesis that is benchmarked against real world case studies. Surrogates, such as patent citation, do serve a useful purpose to assist in the understanding of the historic nature of the innovation system but they fall short of defining the system completely. This paper seeks to aid in the solidification of a hypothesis of the system of innovation as a complex adaptive system. Initial consideration is directed towards the historic interactions that have taken place in the system of innovation. These interactions are viewed through the surrogate of patent citation as there is little other record of innovation. The novelty of this paper is that patent citations form not the core but rather a starting point for the definition of innovation as a complex adaptive system. Various models are built using techniques of cellular automata as well as agent-based modeling to assist in the understanding of the principles at work in the innovation system. These models present startling evidence that there exists an upper bound on the number of interactions any one invention should utilize in its course towards being deemed an innovation. Additionally, the models describe the benefits of partnership between innovating entities in a rapidly changing marketplace such as the current technological markets. This paper asserts specific conclusions, from the models, that assist in understanding that the system of innovation is truly a complex adaptive system. The models are further supported through real world examples.

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Brosi, Dennis. "Examining Emergent Strategy Approaches With Complex Adaptive Systems Principles." St. Gallen, 2009. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/03604899101/$FILE/03604899101.pdf.

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Choe, Sehyo Charley. "Models of complex adaptive systems with underlying network structure." Thesis, University of Oxford, 2007. https://ora.ox.ac.uk/objects/uuid:1cb8cb96-d27f-4543-9065-0e38a4297435.

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This thesis explores the effect of different types of underlying network structure on the dynamical behaviour of a competitive population - a situation encountered in many real-world complex systems. In the first part of the thesis, I focus on generic, but abstract, multi-agent systems. I start by presenting analytic and numerical results for a population of heterogeneous, decision-making agents competing for some limited global resource, in which connections arise unintentionally between agents as a by-product of their strategy choices. I show that accounting for the resulting groups of strongly-correlated agents - in particular, the crowds and so-called 'anticrowds' - yields an accurate analytic description of the systems dynamics. I then introduce a local communication network between the agents, enabling them to intentionally share information among themselves. Such an interaction network leads to highly non-trivial dynamics, forcing a trade-off between individual and global success. Introducing corruption into the information being exchanged between agents, gives rise to a novel phase transition. I then provide a quantitative analytic theory of these various numerical results by generalizing the Crowd-Anticrowd formalism to include such local interactions. In the second part of the thesis, I consider a real-world system which also features competitive populations and networks - a cancer tumour, which contains cancerous cells competing for space and nutrients in the presence of an underlying vasculature structure. To simplify the analysis and comparison to real clinical data, the model chosen is far simpler than that discussed in the first part of the thesis - however despite its simplicity, the model is shown to yield remarkably good agreement with empirical findings. In addition, the model shows how different treatment methods can lead to a wide variety of unexpected re-growth behaviours of the tumour.

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Laine, Tei. "Agent-based model selection framework for complex adaptive systems." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3229580.

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Thesis (Ph.D.)--Indiana University, Computer Science and Cognitive Science, 2006.
"Title from dissertation home page (viewed July 10, 2007)." Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4523. Adviser: Filippo Menczer.

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Chow, Fung-kiu, and 鄒鳳嬌. "Modeling the minority-seeking behavior in complex adaptive systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29367487.

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20

Sullivan, John P. "Emergent Learning: Three Learning Communities as Complex Adaptive Systems." Thesis, Boston College, 2009. http://hdl.handle.net/2345/663.

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Thesis advisor: Patrick J. McQuillan
In the 2007-2008 school year, the author conducted a collaborative case study (Stake, 2000) with the goal of discovering and describing "emergent learning" in three high school classrooms. Emergent learning, defined as the acquisition of new knowledge by an entire group when no individual member of the group possessed it before, is implied by the work of many theorists working on an educational analog of a natural phenomenon called a complex adaptive system. Complex adaptive systems are well networked collectives of agents that are non-linear, bounded and synergistic. The author theorized that classes that maximized the features of complex adaptive systems could produce emergent learning (a form of synergy), and that there was a continuum of this complexity, producing a related continuum of emergence. After observing a co-curricular jazz group, an English class, and a geometry class for most of one academic year, collecting artifacts and interviewing three students and a teacher from each class, the author determined that there was indeed a continuum of complexity. He found that the actively complex nature of the Jazz Rock Ensemble produced an environment where emergence was the norm, with the ensemble producing works of music, new to the world, with each performance. The English section harnessed the chaotic tendencies of students to optimize cognitive dissonance and frequently produce emergent learning, while the mathematics section approached the learning process in a way that was too rigidly linear to allow detectable emergence to occur
Thesis (PhD) — Boston College, 2009
Submitted to: Boston College. Lynch School of Education
Discipline: Teacher Education, Special Education, Curriculum and Instruction

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Sommerer, Christa. "Modeling complex adaptive systems and complexity for interactive art." Thesis, University of South Wales, 2002. https://pure.southwales.ac.uk/en/studentthesis/modeling-complex-adaptive-systems-and-complexity-for-interactive-art(3d7143e3-eb05-49b9-8965-0ffa53767eb9).html.

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Complex System Sciences, as a field of research, has emerged in the past decade. It studies how parts of a system give rise to the collective behaviours of the system and how the system interacts with its environment. It approaches the question of how life on earth could have appeared by searching for inherent structures in living systems and trying to define common patterns within these structures. Complex Systems are also often described as systems where the whole is more complex than the mere sum of its parts, and these systems are also considered to be at the point of maximum computational ability, maximum fitness and maximum evolvability. Several scientific models have simulated Complex Adaptive Systems. These try to model the emergence of complexity within computer-simulated environments inhabited by artificially evolving organisms. My objective in this thesis is to study the application of Complex Systems and Complex Adaptive Systems to Interactive Art and to test how one could construct interactive systems that can create dynamic and open-ended image structures that increase in complexity as users interact with them. Ideally, these interactive artworks should become comparable to Complex Adaptive Systems or even become Complex Systems themselves by satisfying some of the key properties of such systems.

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Ram, Kadambari. "A Complex Systems Simulation Study for Increasing Adaptive-Capacity." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/4477.

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Examination of empirical research confirmed that climate change is a complex problem of anthropological origin and revealed the need for a management framework to facilitate strategic decisions aimed at mitigating a rise in global temperatures of 2-°C linked to irresponsible and unsustainable business practices. The purpose of this simulation study was to develop a management framework of resilience, robustness, sustainability, and adaptive-capacity (RRSA) for organizations viewed as complex systems to address the current unsustainable state. As such, the evolutionary-RRSA prisoner's dilemma (PD) simulation was developed using an evolutionary game theory approach to agent based modeling and simulation, to generate data. Regression analyses tested the relationships between organizational resilience (x1), robustness (x2), and sustainability (x3) as independent variables, and the dependent variable of adaptive capacity (y) for cooperative and defective strategies. The findings were that complex nonlinear relationships exist between resilience, robustness, sustainability, and adaptive-capacity, which is sensitive to initial conditions and may emerge and evolve from combinations of cooperative and defective decisions within the evolutionary RRSA PD management tool. This study resulted in the RRSA management framework, a cyclical 4-phased approach, which may be used by climate governance leaders, negotiators, and policy-makers to facilitate strategy to move global climate change policy forward by guiding bottom-up consumption and production of GHGs, thereby improving adaptive-capacity, while mitigating an increase in global temperatures of 2-°C, which in turn would improve global socio-economic conditions.

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Prasad, Kumkum. "Organisations as complex adaptive systems : implications for the design of information systems." Thesis, Open University, 1998. http://oro.open.ac.uk/57909/.

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Today a paradigm shift in the field of organisation and management theories is no longer disputed and the need to switch from the Command-and-Control to the Leaming Organisation Paradigm (LOP) in the area of organisational theory is well understood. However, it is less well appreciated that learning organisations cannot operate effectively if supported by centralised databases and tailor-made application programs. LOP emphasises adaptability, flexibility, participation and learning. It is important to understand that the changes in organisational and management strategies will not on their own be able to produce the desired effects unless they are supported by appropriate changes in organisational culture, and by effective information systems. This research demonstrates that conventional information system strategies and development methods are no longer adequate. Information system strategies must respond to these needs of the LOP and incorporate new information systems that are capable of evolving, adapting and responding to the constantly changing business environment. The desired adaptability, flexibility and agility in information systems for LOP can be achieved by exploiting the technologies of the Internet, World Wide Web, intelligent agents and intranets. This research establishes that there is a need for synergy between organisational structures and organisational information systems. To obtain this desired synergy it is essential that new information systems be designed as an integral part of the learning organisational structure itself. Complexity theory provides a new set of metaphors and a host of concepts for the understanding of organisations as complex adaptive systems. This research introduces the principles of Complex Adaptive Systems and draws on their significance for designing the information systems needed to support the new generation of learning organisations. The search for new models of information system strategies for today's dynamic world of business points to the 'swarm models' observed in Nature.

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McQuesten, Pamela Ann. "Human action in mass communication : a complex adaptive systems approach /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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25

George, David Frederick James. "Reconfigurable cellular automata computing for complex systems on the SPACE machine /." Connect to this title, 2005. http://theses.library.uwa.edu.au/adt-WU2006.0020.

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26

Yoder-Bontrager, Daryl. "Nongovernmental organizations in disaster and coordination| A complex adaptive systems view." Thesis, University of Delaware, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1585187.

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Анотація:

Nongovernmental organizations (NGOs) play a major role in disasters around the world. As they carry out disaster work NGOs are often grouped together as the "NGO sector," although their varied size, scope, focus and country of origin make generalizations difficult. Coordinating NGO disaster work has been an ongoing challenge for governments and for NGOs themselves for reasons ranging from the wishes of NGO funders to uncertainty about what coordination means to competition for funds.

This thesis uses a complex adaptive system (CAS) framework to understand how NGOs may coordinate their own work. A complex adaptive system is made up of a set of independent agents that interact with each other to form a whole entity without the benefit of an explicit central control mechanism.

The qualitative study carried out semi-structured interviews with 16 NGOs active in disaster in Honduras to explore to what extent their interactions conformed to six characteristics of complex adaptive systems - 1) schemata; 2) self-organization; 3) communication and information; 4) rules; 5) learning and adaptation; and 6) aggregate outcomes, and relations with government.

Results of the interviews showed that many NGOs have multiple links among themselves with active communication channels that depend heavily on personal relationships. Interviews showed that collaboration among NGOs has increased over the past decade, although the degree of cooperation among them was inconsistent. Interviewees found it difficult to name an aggregate system-wide outcome. Government relations were found to be mixed - many NGOs had both positive and negative things to say about their relationships with government.

The NGOs were found to have both characteristics of a CAS and factors that did not fit a CAS description. NGOs must continually invest energy to maintain a system because entropic forces away from increased organization remain strong.

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27

Ho, Ki-hiu, and 何其曉. "Extracting real market behavior in complex adaptive systems through minority game." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B30163705.

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28

Dickens, Peter Martin. "Facilitating Emergence: Complex, Adaptive Systems Theory and the Shape of Change." Antioch University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1339016565.

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29

Chaoui, Hicham. "Soft-computing based intelligent adaptive control design of complex dynamic systems." Thèse, Université du Québec à Trois-Rivières, 2011. http://depot-e.uqtr.ca/2676/1/030295752.pdf.

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30

Onik, Mohammad Fakhrul Alam. "Business value of information technology: A complex adaptive systems theory view." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/132323/1/Mohammad%20Fakhrul%20Alam_Onik_Thesis.pdf.

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This thesis explores a dynamic perspective on the business value of IT (BVIT) in contemporary organisations. Using two theoretical concepts from Complex Adaptive Systems theory, emergence and coevolution, it presents a conceptual BVIT framework explaining how IT-enabled capabilities emerge from IT assets in contemporary organisations and how the coevolution of these capabilities can help organisations obtain competitive advantage. The emergence perspective demonstrates how IT-enabled capabilities arise via bottom-up interactions between the components of IT assets and organisational resources. The coevolution perspective includes micro coevolution, which emphasises how these capabilities improve within organisations, and macro coevolution, which highlights action-based competitive relationships among firms and how they vie for advantage.

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31

Fath, Janet Louise. "An architecture for adaptive computer-assisted instruction programs for complex dynamic systems." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/33442.

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32

Liu, Ying. "Complex-valued adaptive digital signal enhancement for applications in wireless communication systems." Doctoral diss., University of Central Florida, 2012. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/5405.

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In recent decades, the wireless communication industry has attracted a great deal of research efforts to satisfy rigorous performance requirements and preserve high spectral efficiency. Along with this trend, I/Q modulation is frequently applied in modern wireless communications to develop high performance and high data rate systems. This has necessitated the need for applying efficient complex-valued signal processing techniques to highly-integrated, multi-standard receiver devices. In this dissertation, novel techniques for complex-valued digital signal enhancement are presented and analyzed for various applications in wireless communications. The first technique is a unified block processing approach to generate the complex-valued conjugate gradient Least Mean Square (LMS) techniques with optimal adaptations. The proposed algorithms exploit the concept of the complex conjugate gradients to find the orthogonal directions for updating the adaptive filter coefficients at each iteration. Along each orthogonal direction, the presented algorithms employ the complex Taylor series expansion to calculate time-varying convergence factors tailored for the adaptive filter coefficients. The performance of the developed technique is tested in the applications of channel estimation, channel equalization, and adaptive array beamforming. Comparing with the state of the art methods, the proposed techniques demonstrate improved performance and exhibit desirable characteristics for practical use. The second complex-valued signal processing technique is a novel Optimal Block Adaptive algorithm based on Circularity, OBA-C. The proposed OBA-C method compensates for a complex imbalanced signal by restoring its circularity. In addition, by utilizing the complex Taylor series expansion, the OBA-C method optimally updates the adaptive filter coefficients at each iteration. This algorithm can be applied to mitigate the frequency-dependent I/Q mismatch effects in analog front-end. Simulation results indicate that comparing with the existing methods, OBA-C exhibits superior convergence speed while maintaining excellent accuracy. The third technique is regarding interference rejection in communication systems. The research on both LMS and Independent Component Analysis (ICA) based techniques continues to receive significant attention in the area of interference cancellation. The performance of the LMS and ICA based approaches is studied for signals with different probabilistic distributions. Our research indicates that the ICA-based approach works better for super-Gaussian signals, while the LMS-based method is preferable for sub-Gaussian signals. Therefore, an appropriate choice of interference suppression algorithms can be made to satisfy the ever-increasing demand for better performance in modern receiver design.
Ph.D.
Doctorate
Electrical Engineering and Computer Science
Engineering and Computer Science
Electrical Engineering

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33

Guo, Donghang. "Large-Scale Simulations for Complex Adaptive Systems with Application to Biological Domains." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26403.

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Modeling or simulating Complex Adaptive Systems (CASs) is both important and challenging. As the name suggests, CASs are systems consisting of large numbers of interacting adaptive compartments. They are studied across a wide range of disciplines and have unique properties. They model such systems as multicellular organisms, ecosystems, social networks, and many more. They are complex, in the sense that they are dynamical, nonlinear, and heterogeneous systems that cannot be simply scaled up/down. However, they are self-organized, in the sense that they can evolve into specific structures/patterns without guidance from outside sources. Modeling/Simulating CASs is challenging, not only because of the high complexity, but also because of the difficulty in explaining the underlying mechanism behind self-organization. The goal of this research is to provide a modeling framework as well as a simulation platform to advance the study of CASs. We argue that there are common principles behind self-organization processes of different systems across different domains. We explore, analyze, and perform experiments into these principles. We propose and implement modeling templates such as short-term and long-term adaptivity. We incorporate techniques from systems theory, employing computing paradigms, including multi-agent system and asynchronous message passing. We also consider an application from the biological domain to model and simulate under our framework, treating it as a CAS for validation purposes.
Ph. D.

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34

Lentenbrink, Laura. "The Impact of Adaptive Leadership Capacity on Complex Organizational Health Systems Outcomes." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/3619.

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Nonlinear and chaotic environmental changes characterize health services organizations as complex adaptive systems in which leaders must exercise non-traditional leadership practices to succeed. Health services leaders who have learned and implemented traditional linear management approaches are ill prepared to lead in complex environments. This study tested complexity and adaptive leadership theories of agility and resilience in complex health systems. The purpose of this quantitative cross-sectional internet-based survey study was to quantify relationships between independent variables of agility and resilience and secondary dependent variables of financial, patient satisfaction, quality and human capital outcomes. The impact of turbulence was also examined. Included sample data were collected from 533 employed healthcare leaders using probability-based systematic proportional random sampling methods and were analyzed through correlation, regression, one-way analysis of variance, t tests, and Hayes PROCESS statistical analytics. Agility correlated with and predicted patient satisfaction outcomes. Resilience independently correlated with and predicted financial performance and patient satisfaction outcomes and augmented the correlation and predictability of agility. Agility and resilience cumulatively predicted financial performance outcomes. Turbulence was related to agility, resilience, financial performance, and patient care quality outcomes and mediated relationships with financial and patient care quality outcomes. Health services leaders may apply these findings to promote social change through the implementation of the agile and resilient leadership approaches necessary to achieve organizational performance outcomes that benefit vulnerable populations.

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35

Nel, Darren Henry. "Exploring a complex adaptive systems approach to the study of urban change." Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/56093.

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Cities are one of humankind s more enduring creations. Although historically cities have perished, urbanism has not; declining urban areas have either revived or new cities have taken their place. Additionally, with the increasing rate of urbanisation cities have not only increased in number but also in size, while simultaneously their impact on the environment has grown, giving rise to debate on the sustainability of cities. However, this becomes a difficult task given that our cities are experiencing unprecedented challenges, of rapid urbanisation, strained and aging infrastructure, social unrest, and the increasing impacts and concerns of climate change. The need for cities to adapt or die has never been greater. The concept of resilience presents a possible solution to help deal with this unpredictable nature of the future. It refers to a system s (a city for example) ability to withstand sudden shocks, like floods, while at the same time having the capacity to adapt to long?term, incremental, changes, like climate change and global warming. As the concept of resilience has become ever more popular within the scientific and planning community, the need to understand this concept and its implications is becoming more important. However, to do this we must first take a step back and understand the theoretical principles/foundations on which resilience theory has been built. Resilience is an emergent property of complex adaptive systems (CAS). Thus, to understand resilience, we must first understand CAS. Complexity theory seeks to understand how complex systems work. One of the ways that complexity theory does this is by understanding properties and mechanisms that allow complex systems to function and survive. Cities can be described as complex adaptive systems as they are undeniably complex and exhibit the same properties that can be found in any CAS. Through the study of social?ecological systems (SES), which are also CAS, researchers have identified that social?ecological systems go through periodic cycles of change, each cycle with its own identifiable characteristics. These cycles of change have been described through the concepts of Panarchy' and the Adaptive Cycle . This study seeks to apply these concepts to the study of urban change in an attempt to test their usefulness in understanding the urban system and how it changes. The concepts from complexity theory and SES theory have been brought together and presented in this study in the form of a framework. The aim of the framework is to describe the urban system and how it changes. The proposed framework has potential to be both a useful theoretical construct and, with some adaptions, a useful tool or manual for practitioners in the field who need to make sense of the complex environments in which they find themselves. It is expected that the framework will become another instrument in a planner s toolbox by means of which they can make better informed decisions.
Dissertation (MTRP)--University of Pretoria, 2015.
tm2016
Town and Regional Planning
MTRP
Unrestricted

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36

George, David Frederick James. "Reconfigurable cellular automata computing for complex systems on the SPACE machine." University of Western Australia. School of Computer Science and Software Engineering, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0020.

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Many complex natural and man made systems are inherently concurrent in nature, consisting of many autonomous parts that interact with each other. Cellular automata allow the concurrency and interactions of these complex systems to be modelled. Using a reconfigurable a computing platform for running cellular automata models allows the natural concurrency of digital electronics to be directly exploited by the system being modelled. This thesis investigates methods and philosophies for developing cellular automata models on a reconfigurable computing platform, the SPACE machine. Modelling and verification techniques are developed using a process algebra, Circal. These techniques allow the desired behaviour of a system to be specified and simulated. The model is then translated into a digital design, which can be verified as correct against the behavioural model using the Circal system. Three cellular automata system are used to develop the methods and philosophies. The Game of Life is used to investigate how to model and implement CA on the SPACE machine. The Philosophies and techniques that are developed for the Game of Life are used in the following systems. More complex cellular automata models of road traffic are used to further develop the modelling techniques developed in the Game a Life. A user interface, which was created for viewing the outputs from the Game a Life, is extended to allow cellular automata cells to be dynamically placed and moved about on the computing surface, allowing the user to observe and modify experiment in real time. A cellular automata based cryptography system is then used to further enhance the techniques developed, and particularly to explore the area of producing dynamically reconfigured circuits as the inputs to the system change. The thesis concludes that there are many real life complex systems, such as road traffic simulation and cryptography, which require high performs systems to run on. The methods and philosophies developed in this thesis allow CA systems to be modelled using process algebra and run directly in digital hardware, allowing the natural concurrency of the hardware to be fully exploited.

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37

Major, Sarah J. "Building Resilience: A Complex Systems Approach to Sustainable Design." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337363724.

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38

Espinosa, Jennifer Anne. "Understanding the Complexity of Product Returns Management: A Complex Adaptive Systems Theory Perspective." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6233.

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Анотація:

The core essence of a marketing transaction is the exchange of value between two parties. Quite often, the exchange of value describes a customer purchasing a product from a company. When purchasing products, the exchange of value can often fail due to product defects or customer dissatisfaction. When the marketing exchange fails, customers often desire an avenue for recourse to right the exchange imbalance. Accepting and quickly processing product returns represents a strategic tool companies can leverage to maintain healthy relationships with customers, despite an exchange failure. Effectively managing product returns also benefits companies financially, by reducing inventory levels, costs, and the risk of product obsolescence. Despite providing both relationship management and financial benefits, numerous companies struggle to manage product returns effectively. In a time when companies are facing a growing number of product returns due to omni-channel retailing and online shopping, implementing an effective system to manage product returns has become a vital strategic tool necessary to maintain competitiveness. First, the current research answers the question of why do companies struggle with product returns? by identifying the important components of an effective product returns system. Informed by complex adaptive systems theory and based on a qualitative, grounded theory analysis, the current research finds that the hidden complex nature of managing product returns prevents numerous companies from implementing an effective system to mange returns. Managing product returns requires five important components (firm capabilities, employees, the returns management information system, organizational climate, and the customer service boundary), which interact with each other multiple times to process a product return. After identifying the important components and interactions within a product returns system, Essay I integrates the information together to form a substantive theory of the complexity of product returns management. The substantive theory implies that companies looking to improve their management of product returns need to understand and invest in multiple components within the product returns system. Second, the current research answers the question of how do the employees, returns management information system, and climate for creativity components of a product returns system relate to a firm’s flexibility, adaptability, and performance? To answer this research question, this dissertation empirically evaluates the role these three components play in shaping a firm’s flexibility, adaptability, subjective performance and relationship quality by analyzing data collected through an online survey with 102 US managers with experience in product returns. The empirical analysis indicates that employee decision-making resources show a statistically significant negative relationship with firm adaptability, while the firm’s climate for creativity and flexibility show a statistically significant positive relationship with firm adaptability. Firm adaptability shows statistically significant positive relationships with subjective performance and relationship quality. Firm adaptability acts as a partial or full mediator in all of these relationships. The combined findings of Essay I and Essay II point to the importance of product returns as a strategic relationship management tool. Firms that can effectively manage product returns give employees more flexibility to respond to problems, are better able to make structural changes, have higher subjective performance ratings, and better quality relationships with customers.

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39

Mohamad, Mustafa A. "Direct and adaptive quantification schemes for extreme event statistics in complex dynamical systems." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113542.

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Анотація:

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 171-183).
Quantifying extreme events is a central issue for many technological processes and natural phenomena. As extreme events, we consider transient responses that push the system away from its statistical steady state and that correspond to large excursions. Complex systems exhibiting extreme events include dynamical systems found in nature, such as the occurrence of anomalous weather and climate events, turbulence, formation of freak waves in the ocean and optics, and dynamical systems in engineering applications, including mechanical components under environmental loads, ship rolling and capsizing, critical events in power grids, as well as chemical reactions and conformational changes in molecules. It has been recognized that extreme events occur more frequently than Gaussian statistics suggest and thus occur often enough that they have practical consequences, and sometimes catastrophic outcomes, that are important to understand and predict. A hallmark characteristic of extreme events in complex dynamical systems is non-Gaussian statistics (e.g. heavy-tails) in the probability density function (pdf) describing the response of their observables. For engineers and applied mathematicians, a central issue is how to efficiently and accurately describe this non-Gaussian behavior. For random dynamical systems with inherently nonlinear dynamics, expressed through intermittent events, nonlinear energy transfers, broad energy spectra, and large intrinsic dimensionality, it is largely the case that we are limited to (direct) Monte-Carlo sampling, which is too expensive to apply in real-world applications. To address these challenges, we present both direct and adaptive (sampling based) strategies designed to quantify the probabilistic aspects of extreme events in complex dynamical systems, effectively and efficiently. Specifically, we first develop a direct quantification framework that involves a probabilistic decomposition that separately considers intermittent, extreme events from the background stochastic attractor of the dynamical system. This decomposition requires knowledge of the dynamical mechanisms that are responsible for extreme events and partitions the phase space accordingly. We then apply different uncertainty quantification schemes to the two decomposed dynamical regimes: the background attractor and the intermittent, extreme-event component. The background component, describing the 'core' of the pdf, although potentially very high-dimensional, can be efficiently described by uncertainty quantification schemes that resolve low-order statistics. On the other hand, the intermittent component, related to the tails, can be described in terms of a low-dimensional representation by a small number of modes through a reduced order model of the extreme events. The probabilistic information from these two regimes is then synthesized according to a total probability law argument, to effectively approximate the heavy-tailed, non-Gaussian probability distribution function for quantities of interest. The method is demonstrated through numerous applications and examples, including the analytical and semi-analytical quantification of the heavy-tailed statistics in mechanical systems under random impulsive excitations (modeling slamming events in high speed craft motion), oscillators undergoing transient parametric resonances and instabilities (modeling ship rolling in irregular seas and beam bending), and extreme events in nonlinear Schrodinger based equations (modeling rogue waves in the deep ocean). The proposed algorithm is shown to accurately describe tail statistics in all of these examples and is demonstrated to be many orders of magnitude faster than direct Monte-Carlo simulations. The second part of this thesis involves the development of adaptive, sampling based strategies that aim to accurately estimate the probability distribution and extreme response statistics of a scalar observable, or quantity of interest, through a minimum number of experiments (numerical simulations). These schemes do not require specialized knowledge of the dynamics, nor understanding of the mechanism that cause or trigger extreme responses. For numerous complex systems it may not be possible or very challenging to analyze and quantify conditions that lead to extreme responses or even to obtain an accurate description of the dynamics of all the processes that are significant. To address this important class of problems, we develop a sequential algorithm that provides the next-best design point (set of experimental parameters) that leads to the largest reduction in the error of the probability density function estimate for the scalar quantity of interest when the adaptively predicted design point is evaluated. The proposed algorithm utilizes Gaussian process regression to infer dynamical properties of the quantity of interest, which is then used to estimate the desired pdf along with uncertainty bounds. We iteratively determine new design points through an optimization procedure that finds the optimal point in parameter space that maximally reduces uncertainty between the estimated bounds of the posterior pdf estimate of the observable. We provide theorems that guarantee convergence of the algorithm and analyze its asymptotic behavior. The adaptive sampling method is illustrated to an example in ocean engineering. We apply the algorithm to estimate the non-Gaussian statistics describing the loads on an offshore platform in irregular seas. The response of the platform is quantified through three-dimensional smoothed particle hydrodynamics simulations. Because of the extreme computational cost of these numerical models, quantification of the extreme event statistics for such systems has been a formidable challenge. We demonstrate that the adaptive algorithm accurately quantifies the extreme event statistics of the loads on the structure through a small number of numerical experiments, showcasing that the proposed algorithm can realistically account for extreme events in the design and optimization processes for large-scale engineering systems.
by Mustafa A. Mohamad.
Ph. D.

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40

Murray, D. "Real-time stimulation for exercising complex systems employing adaptive sensors and sensor arrays." Thesis, University College London (University of London), 2013. http://discovery.ucl.ac.uk/1397142/.

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This research investigates the current structure of the Ministry of Defence's procurement system, with particular emphasis on the procurement of military sensor systems. A lifecycle common test environment, with an appropriate commercial construct for its implementation, is proposed. Sensor systems include radar, passive RF surveillance (ESM) as well as electro-optic, infrared, sonar and other acoustic monitoring systems that are used to gather intelligence for a number of purposes including 1. Pre-empting hostile acts 2. Reducing risk to friendly forces and non-combatants in danger zones 3. Informing and prosecuting attacks on hostile forces Sensor systems often form part of larger systems, also called systems of systems. In some cases, a number of sensors are required to work together to improve information extraction by data or information fusion. It will be seen that these are complex systems. They are often designed to adapt their modes of operation to meet evolving situations. In this way, they can optimise themselves to meet their deployment objectives. These are difficult systems to specify. Therefore, they are difficult systems to test; they are expected to respond to a large number of situations that cannot easily be defined in advance of their being encountered. This research brings together technical and commercial initiatives to remove many of the existing discontinuities along the lifecycle of such projects. The discontinuities harbour technical and commercial discrepancies that detract from achieving delivery and cost targets. A pragmatic Test and Evaluation concept is defined. It is backed by a commercial process. Together they provide an independent way to deliver continuous lifecycle evaluation and test of sensor systems. This research offers a quantifiable measure of military capability improvements that complies with Systems Engineering and Management good practice.

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41

Whiteley, Jervis. "Complex Adaptive Systems and Conversation Analysis: A New Perspective for Consumer Behaviour Research?" Thesis, Curtin University, 2002. http://hdl.handle.net/20.500.11937/734.

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Анотація:

The research question for this study is “Can concepts from complex adaptive systems and conversation analysis be used to research consumer behaviour?" This is, primarily, a theoretical question. After a wide-ranging literature search no scholarly publications linking the qualitative aspects of complex adaptive systems theory to marketing or consumer research were located. In addition, there appear to be few papers on consumer research which use conversation analysis. A theory for the research methodology was developed. It was argued that the production of a research theory and methodology to test the relevance and appropriateness of two very different theories - complex adaptive systems and conversation analysis was the major undertaking of this thesis. The problem of combining an essentially scientific perspective (complex adaptive systems) with an essentially qualitative one (ethnomethodology and conversation analysis) was resolved as part of the research process. A bridging theory was developed through the common ground offered by the sociology of scientific knowledge on the one hand and social-constructionist theory on the other. This methodology was successful in supporting the choice of conversation analysis as the data-collection method and provided the rationale for observing five characteristics of a complex adaptive system. The methodology was tested empirically and, in keeping with exploratory work, iteratively. It is not intended that this type of research will have predictive value. The complex adaptive system studied was consumers in a small group. There were two research locations with six data-collection sessions in each. The first location collected data from organisational groups. The second collected data from groups of consumers convened in a meeting room.Data were transcribed and analysed for all sessions according to the conventions of conversation analysis. In the meeting-room sessions, data were also collected by electronic-group-support-systems technology and subjected to a modified form of content analysis. The broad findings showed the following. The assumption that there was little evidence of interest in complex adaptive systems among consumer behaviour researchers was confirmed. Apart from one paper calling for the use of conversation analysis in consumer behaviour research, there appeared to have been no subsequent reports of its adoption. The potential for conversation analysis in consumer research has probably not been understood because it was seen as a data-collection method only within an ethnomethodological perspective. The discursive theoretical perspective, which gives a prime position to conversation analysis in the construction of factual accounts, was found to be an innovative way to study consumer behaviour. A discursive theoretical research perspective could have provided a more robust theoretical justification for the fieldwork carried out in this study than the theory of the methodology that was first developed for this study. Conversation analysis did meet the five criteria proposed for surfacing a complex adaptive system in a small group but in an unexpected way. It met these criteria through the research process. In other words, by setting up an appropriate research environment and using conversation analysis, it was shown that a complex adaptive system was in operation.An outcome of employing complex adaptive systems theory and conversation analysis is a new way of seeing groups of consumers as a self-organised, nonlinear, interactive entity. Conversation analysis has proven to be a method of empirically observing this entity, whilst preserving the consumer groups' complex adaptiveness. There were three conclusions. The first is that the discursive paradigm appears to be an alternative paradigm for consumer behaviour research that is appropriate for certain applications. For example, marketing communications and word-of-mouth communication. The second conclusion is that when small-group talk-in-interaction is recorded and analysed using conversation analysis, the characteristics of a complex adaptive system theorised in this study seem evident to the researcher. The third is that complex adaptive systems appear to be capable of being researched in the field, but more work is needed on defining the characteristics to be researched.

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42

Whiteley, Jervis. "Complex Adaptive Systems and Conversation Analysis: A New Perspective for Consumer Behaviour Research?" Curtin University of Technology, Graduate School of Business, 2002. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=12936.

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Анотація:

The research question for this study is “Can concepts from complex adaptive systems and conversation analysis be used to research consumer behaviour?" This is, primarily, a theoretical question. After a wide-ranging literature search no scholarly publications linking the qualitative aspects of complex adaptive systems theory to marketing or consumer research were located. In addition, there appear to be few papers on consumer research which use conversation analysis. A theory for the research methodology was developed. It was argued that the production of a research theory and methodology to test the relevance and appropriateness of two very different theories - complex adaptive systems and conversation analysis was the major undertaking of this thesis. The problem of combining an essentially scientific perspective (complex adaptive systems) with an essentially qualitative one (ethnomethodology and conversation analysis) was resolved as part of the research process. A bridging theory was developed through the common ground offered by the sociology of scientific knowledge on the one hand and social-constructionist theory on the other. This methodology was successful in supporting the choice of conversation analysis as the data-collection method and provided the rationale for observing five characteristics of a complex adaptive system. The methodology was tested empirically and, in keeping with exploratory work, iteratively. It is not intended that this type of research will have predictive value. The complex adaptive system studied was consumers in a small group. There were two research locations with six data-collection sessions in each. The first location collected data from organisational groups. The second collected data from groups of consumers convened in a meeting room.
Data were transcribed and analysed for all sessions according to the conventions of conversation analysis. In the meeting-room sessions, data were also collected by electronic-group-support-systems technology and subjected to a modified form of content analysis. The broad findings showed the following. The assumption that there was little evidence of interest in complex adaptive systems among consumer behaviour researchers was confirmed. Apart from one paper calling for the use of conversation analysis in consumer behaviour research, there appeared to have been no subsequent reports of its adoption. The potential for conversation analysis in consumer research has probably not been understood because it was seen as a data-collection method only within an ethnomethodological perspective. The discursive theoretical perspective, which gives a prime position to conversation analysis in the construction of factual accounts, was found to be an innovative way to study consumer behaviour. A discursive theoretical research perspective could have provided a more robust theoretical justification for the fieldwork carried out in this study than the theory of the methodology that was first developed for this study. Conversation analysis did meet the five criteria proposed for surfacing a complex adaptive system in a small group but in an unexpected way. It met these criteria through the research process. In other words, by setting up an appropriate research environment and using conversation analysis, it was shown that a complex adaptive system was in operation.
An outcome of employing complex adaptive systems theory and conversation analysis is a new way of seeing groups of consumers as a self-organised, nonlinear, interactive entity. Conversation analysis has proven to be a method of empirically observing this entity, whilst preserving the consumer groups' complex adaptiveness. There were three conclusions. The first is that the discursive paradigm appears to be an alternative paradigm for consumer behaviour research that is appropriate for certain applications. For example, marketing communications and word-of-mouth communication. The second conclusion is that when small-group talk-in-interaction is recorded and analysed using conversation analysis, the characteristics of a complex adaptive system theorised in this study seem evident to the researcher. The third is that complex adaptive systems appear to be capable of being researched in the field, but more work is needed on defining the characteristics to be researched.

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43

Viveca, Lindahl. "Optimizing sampling of important events in complex biomolecular systems." Doctoral thesis, KTH, Fysik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-217837.

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Proteins and DNA are large, complex molecules that carry out biological functions essential to all life. Their successful operation relies on adopting specific structures, stabilized by intra-molecular interactions between atoms. The spatial and temporal resolution required to study the mechanics of these molecules in full detail can only be obtained using computer simulations of molecular models. In a molecular dynamics simulation, a trajectory of the system is generated, which allows mapping out the states and dynamics of the molecule. However, the time and length scales characteristic of biological events are many orders of magnitude larger than the resolution needed to accurately describe the microscopic processes of the atoms. To overcome this problem, sampling methods have been developed that enhance the occurrence of rare but important events, which improves the statistics of simulation data. This thesis summarizes my work on developing the AWH method, an algorithm that adaptively optimizes sampling toward a target function and simultaneously finds and assigns probabilities to states of the simulated system. I have adapted AWH for use in molecular dynamics simulations. In doing so, I investigated the convergence of the method as a function of its input parameters and improved the robustness of the method. I have also worked on a generally applicable approach for calculating the target function in an automatic and non-arbitrary way. Traditionally, the target is set in an ad hoc way, while now sampling can be improved by 50% or more without extra effort. I have also used AWH to improve sampling in two biologically relevant applications. In one paper, we study the opening of a DNA base pair, which due to the stability of the DNA double helix only very rarely occurs spontaneously. We show that the probability of opening depends on both nearest-neighbor and longer-range sequence effect and furthermore structurally characterize the open states. In the second application the permeability and ammonia selectivity of the membrane protein aquaporin is investigated and we show that these functions are sensitive to specific mutations.

QC 20171117

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44

Oliver, John M. "Multi-objective optimisation methods applied to complex engineering systems." Thesis, Cranfield University, 2014. http://dspace.lib.cranfield.ac.uk/handle/1826/11707.

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This research proposes, implements and analyses a novel framework for multiobjective optimisation through evolutionary computing aimed at, but not restricted to, real-world problems in the engineering design domain. Evolutionary algorithms have been used to tackle a variety of non-linear multiobjective optimisation problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the number of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimising evolutionary algorithm framework, incorporating a genetic algorithm, that uses self-adaptive mutation and crossover in an attempt to avoid such problems, and which has been benchmarked against both standard optimisation test problems in the literature and a real-world airfoil optimisation case. For this last case, the minimisation of drag and maximisation of lift coefficients of a well documented standard airfoil, the framework is integrated with a freeform deformation tool to manage the changes to the section geometry, and XFoil, a tool which evaluates the airfoil in terms of its aerodynamic efficiency. The performance of the framework on this problem is compared with those of two other heuristic MOO algorithms known to perform well, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this framework achieves better or at least no worse convergence. The framework of this research is then considered as a candidate for smart (electricity) grid optimisation. Power networks can be improved in both technical and economical terms by the inclusion of distributed generation which may include renewable energy sources. The essential problem in national power networks is that of power flow and in particular, optimal power flow calculations of alternating (or possibly, direct) current. The aims of this work are to propose and investigate a method to assist in the determination of the composition of optimal or high-performing power networks in terms of the type, number and location of the distributed generators, and to analyse the multi-dimensional results of the evolutionary computation component in order to reveal relationships between the network design vector elements and to identify possible further methods of improving models in future work. The results indicate that the method used is a feasible one for the achievement of these goals, and also for determining optimal flow capacities of transmission lines connecting the bus bars in the network.

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Malik, Pravir. "Development and evaluation of a framework for an engine of innovation in complex adaptive systems." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/62779.

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The emerging, multi-disciplinary field of Complex Adaptive Systems (CAS) is an alternative to linear, reductionist thinking. It is based on the observations that real-world systems, regardless of scale, are emergent, complex, adaptive, and evolutionary. In this research the scale of CAS examined range from distances of Planck’s constant to Gigaparsecs. CAS has also heavily leveraged the interpretations of several recent Nobel Laureates and assumes too that the world is random, indeterministic, and chaotic. But randomness, chaos, and indeterminism can hardly create the progressive, increasingly harmonious world that we are a part of. At the heart of this issue lies confusion around what innovation in CAS really is. The essential approach to arriving at a mathematical basis of innovation for CAS here has been to view systems from the outside-in as opposed to from the inside-out and the bottom-up. In this approach innovation is conceptualized as existing in every single space-time point-instant in a system. There is a process of precipitation by which this innovation may express itself through a series of quaternary-based architectural forces that are the prime sources of innovation. These series or arrays of forces may further precipitate by informing organizational signatures. Organizations can be thought of as formations with a unique signature at their center, and can vary in complexity and scale. The unique signature for each organization is usually hidden though by common surface dynamics, and “to innovate” is to work through and change the habitual and common patterns in order to allow the deeper founts of innovation to become active at the surface level. When this happens, it is then that innovation occurs. Once that is more clearly seen then the erected probabilistic and uncertainty functions assumed to be true of the fundamental layers of nature, will be relegated to their place as interim devices in model building. The nature of innovation can be progressively elaborated through inductive reasoning to arrive at a mathematical framework for innovation in CAS. Rather than assume a chaotic, random, indeterministic world as a starting point, this framework can be built assuming a purposeful, ordered world characterized by qualified determinism. Equations to provide insight into the inherent innovation bias of our system, the nature of each point in the system, the broad architectural forces behind the development of organizations, the inherent uniqueness of each organization, the way to think about varying cultures or organizations, and the inherent dynamism of our system, form the edifice of this framework. The resulting model can then be used deductively to reinforce observations, and predictively to suggest directions and / or steps to emerging trends. This research hence, through deriving mathematical equations, and by further applying these to various domains ranging from the quantum, to the atomic, to the cellular, to the astrophysical, has been able to provide mathematical contributions to the theory of CAS and to various CAS application areas. With respect to the theory of CAS, mathematical contributions have been made to understanding the underlying directional bias of CAS activity, understanding the nature of each point in any CAS, and creating mathematical sets for architectural forces that are posited to be behind the development of any CAS. Further, mathematical contributions have been made to understanding the inherent dynamics in any CAS, the dynamics of stagnation and growth in CAS, and the balance of randomness and determinism of any CAS. Mathematical contributions also extend to framing complexity in CAS, understanding what can drive sustainability of CAS, and arriving at a general set of mathematical operators true of any CAS. In terms of application areas in the organizational space, mathematical contributions have been made to understanding uniqueness of organizations, the emergence of uniqueness in organizations, and what constitutes varying culture of organizations. Further, existing work done by Nobel Laureate Ilya Prigogine and Alan Turing have been leveraged to further frame organizational transitions, and to frame and model shifts in innovations, respectively. Further mathematical contributions have been made in a range of CAS areas at different scale and level of complexity. Hence, a series of equations have been derived for the electromagnetic spectrum. Quantum, atomic, and cellular wave equations have been derived building off Schrodinger’s existing Wave Equation. Further qualifications have been derived for Heisenberg’s Uncertainty Principle and an equation has been derived for the integration of different layers of CAS also using Heisenberg’s Uncertainty Principle. Equations for space and time alteration as per Einstein’s Theory of Relativity have also been derived. Additionally, equations for the architectures of quantum particles, periodic table elements, and molecular plans at the cellular level have also been derived. Finally, equations for dark matter and dark energy, non-probabilistic quantum states in quantum computing, and the emergence of CAS in the universe have been derived. In all over 225 equations in 25 different areas have been derived in this dissertation. In fact, as suggested by the CAS equation derived for a unified field, everything, from unseen energy fields, to quantum particles, to atoms, to molecules, to cells, and therefore to all animate and even inanimate and even unseen objects, and therefore even any CAS system regardless of scale would have a high-degree of quaternary intelligence embedded in it and exist simultaneously. Quoting Schrodinger: “What we observe as material bodies and forces are nothing but shapes and variations in the structure of space. Particles are just schaumkommen (appearances). The world is given to me only once, not one existing and one perceived. Subject and object are only one. The barrier between them cannot be said to have broken down as a result of recent experience in the physical sciences, for this barrier does not exist.” This implicit quaternary-based intelligence likely sheds new light on properties such as distributed control, uncertainty, paradox, co-evolution, emergence, amongst others, seen as fundamental to CAS. Thinking about CAS as purposeful, and animated by a mathematically-framed engine of innovation, allows existence to potentially be considered as a unified field. Further, it allows insight and additional solutions to a host of complex problems regardless of scale – at the quantum, cellular, human, organizational, sociotechnical, market, economical, political, and social levels - to be conceptualized, designed, elaborated, and managed differently.
Thesis (PhD)--University of Pretoria, 2017.
Graduate School of Technology Management (GSTM)
PhD
Unrestricted

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46

LeMaster, Cheryl Faye. "Leading Change in Complex Systems: A Paradigm Shift." Antioch University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1500033972019138.

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47

Russell, Carol Faculty of Engineering UNSW. "E-learning adoption in a campus university as a complex adaptive system: mapping lecturer strategies." Awarded by:University of Leicester, 2008. http://handle.unsw.edu.au/1959.4/39597.

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The adoption of e-learning technologies in campus universities has not realised its potential for meeting the learning needs and expectations of 21st century students. By modelling university learning and teaching as a complex adaptive system, this thesis develops a new way of understanding and managing the adoption of new learning technologies in campus universities. The literature on learning and teaching in higher education indicates that lecturers??? ability to innovate in their teaching is constrained by tacit and discipline-specific educational knowledge. Introducing new methods and technologies into mainstream university teaching requires explicit review of educational knowledge, and requires support from departmental and institutional organizational systems. Research on organizational change in other contexts, such as manufacturing industry, has used complex adaptive systems modelling to understand the systemic interdependence of individual strategies, organizations and technologies. These models suggest that the integration of new e-learning technologies into mainstream campus university teaching will involve corresponding change processes. Part of this change requires the linking up of diverse disciplinary perspectives on learning and teaching. The thesis develops a conceptual framework for researching university learning and teaching as a complex adaptive system that includes learning technologies, people, and their organization within a university. Complex adaptive systems theory suggests that the capacity of a campus university to adapt to new e-learning technologies will be reflected in patterns in the strategies of those lecturers who are early adopters of those technologies. A context-specific study in the University of New South Wales used cognitive mapping to represent and analyse the strategies of a group of 19 early adopters of e-learning technology. These early adopters were participants in a cross-discipline Fellowship programme intended to develop their ability to act as change agents within the university. Analysis of the maps gathered before and after the Fellowship, triangulated with data on the Fellows??? participation in organizational change, leads to a new way of modelling how university learning and teaching systems, including their technologies, adapt within a complex and changing higher education context.

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Pham, Hoang Anh [Verfasser], and Dirk [Akademischer Betreuer] Söffker. "Contributions to Model-Free Adaptive Control for Complex Mechanical Systems / Hoang Anh Pham ; Betreuer: Dirk Söffker." Duisburg, 2021. http://d-nb.info/122609211X/34.

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49

Deshpande, Aditya. "Robot Swarm Based On Ant Foraging Hypothesis With Adaptive Levy Flights." University of Cincinnati / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1504780906566663.

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au, Helenallison@ozemail com, and Helen Elizabeth Allison. "Linked Social-Ecological Systems: A Case Study of The Resilience of The Western Australian Agricultural Region." Murdoch University, 2003. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20040730.144640.

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In the Western Australian agricultural region, an area of approximately 14 million hectares (70,000 square miles), widespread areas of native vegetation have been cleared and replaced with annual cropping systems, predominantly wheat. Only1.3 million hectares (10%) of small and scattered native vegetation remnants remain. By 2000 16% of land in the region was at risk from soil salinity and was largely unproductive for commercial agriculture. A new hydrological equilibrium affecting 33% of the Western Australian agricultural region is predicted to be reached between 2050 and 2300. The starting premise of this dissertation is that normal disciplinary science was adopted as the dominant intellectual influence on natural resource management policy and thus natural resource degradation was treated as a problem for science, extracted from its social, economic and historical contexts. The second premise of this dissertation is that natural resource problems are not isolated scientific or technical problems, and are exacerbated by human failure to predict the complex inter-relationships among the social, ecological and economic systems. This dissertation initially provides an analytical narrative on the Western Australian agricultural region between 1889 and 2003 (114 years) with the main finding being that in the years pre-1970 a development-driven Western Australian Government was responsible for extensive land clearing for agriculture, often contrary to scientific advice. In the 1980s and 1990s the severity and extent of soil salinity and the prognosis of future negative trends in other natural resource indicators caused a rapid proliferation and evolution of Federal and State policies designed to solve the problem. Nonetheless many natural resource problems remain intractable. The second part of the dissertation investigates the epistemology of the normal science paradigm as it was applied to natural resource management problems in the 20th century as a potentially contributing cause. The evolution of an alternative epistemology, post-normal science paradigm, is then examined for explicating our current understanding of reality. A research framework was constructed which defines the post-normal science paradigm; the systemic approach; the bodies of theoryorganisational, ecology, resilience and system dynamics theory; the social-ecological system perspective; and the methodsresilience analysis and system dynamics. This framework provides a novel way in which to gain a greater understanding of the fundamental or root causes of natural resource management problems. Using the case study of the Western Australian agricultural region a dynamic model was constructed based on descriptive information. An examination of the historical events and processes of the Western Australian agricultural region reveals that over a 114-year history it has evolved through two interactions of the adaptive cycle. Further investigation reveals these two cycles were synchronous with the second and third economic long-wave cycles or Kondratiev Cycles, that show the behaviour over time of the evolution of modern industrial societies. The model suggests that the reasons for the dynamic behaviour of the Western Australian agricultural region lie in the interaction of the three production growth drivers of the international commodity system, which have resulted in a pathological system, the Lock-in Trap. Increased total commodity production, reinvestment and declining prices in real terms have tended to produce the unintended negative impacts of resource decline, environmental pollution and rural population decline. I suggest that the expansion of thresholds through the reinvestment in technology is a principle reason why there has not yet been a profound collapse of exploited renewable resources in the Western Australian agricultural region. Regional natural resource management strategies will need to take account of not only spatial cross-scale issues, in particular the linkages between the individual farmer and the international commodity system, but also the temporal variables, in particular the slowly emerging changes in ecological/physical variables, such as the hydrological cycle. This research can help to provide the information and heuristic metaphors to encourage natural resource policy makers to take long-term and whole system perspectives. It includes a powerful set of tools for communicating dynamic processes in an integrated method to inform policy and management decisions. The ideas in this interdisciplinary research are essential for making science relevant within a social and ecological context.

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Дисертації з теми "Complex adaptive systems (CAS)"

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