The systems theory framework of career development and counseling: Connecting theory and practice

The practice of career counseling has been derived from principles of career theory and counseling theory. In recent times, the fields of both career and counseling theory have undergone considerable change. This article details the move toward convergence in career theory, and the subsequent development of the Systems Theory Framework in this domain. The importance of this development to connecting theory and practice in the field of career counseling is discussed.

A comparison of variational and Markov chain Monte Carlo methods for inference in partially observed stochastic dynamic systems

In recent work we have developed a novel variational inference method for partially observed systems governed by stochastic differential equations. In this paper we provide a comparison of the Variational Gaussian Process Smoother with an exact solution computed using a Hybrid Monte Carlo approach to path sampling, applied to a stochastic double well potential model. It is demonstrated that the variational smoother provides us a very accurate estimate of mean path while conditional variance is slightly underestimated. We conclude with some remarks as to the advantages and disadvantages of the variational smoother. © 2008 Springer Science + Business Media LLC.

Examining the strategy development process through the lens of complex adaptive systems theory

The development of strategy remains a debate for academics and a concern for practitioners. Published research has focused on producing models for strategy development and on studying how strategy is developed in organisations. The Operational Research literature has highlighted the importance of considering complexity within strategic decision making; but little has been done to link strategy development with complexity theories, despite organisations and organisational environments becoming increasingly more complex. We review the dominant streams of strategy development and complexity theories. Our theoretical investigation results in the first conceptual framework which links an established Strategic Operational Research model, the Strategy Development Process model, with complexity via Complex Adaptive Systems theory. We present preliminary findings from the use of this conceptual framework applied to a longitudinal, in-depth case study, to demonstrate the advantages of using this integrated conceptual model. Our research shows that the conceptual model proposed provides rich data and allows for a more holistic examination of the strategy development process. © 2012 Operational Research Society Ltd. All rights reserved.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Cold War Legacies: Systems, Theory, Aesthetics

From futures research, pattern recognition algorithms, nuclear waste disposal and surveillance technologies, to smart weapons systems, contemporary fiction and art, this book shows that we are now living in a world imagined and engineered during the Cold War. Drawing on theorists such as Jean Baudrillard, Jacques Derrida, Michel Foucault, Luce Irigaray, Friedrich Kittler, Michel Serres, Peter Sloterdijk, Carl Schmitt, Bernard Stiegler and Paul Virilio this collection makes connections between Cold War material and conceptual technologies, as they relate to the arts, society, and culture.

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.

Second-order cybernetics and enactive perception

Purpose - To present an account of cognition integrating second-order cybernetics (SOC) together with enactive perception and dynamic systems theory. Design/methodology/approach - The paper presents a brief critique of classical models of cognition then outlines how integration of SOC, enactive perception and dynamic systems theory can overcome some weaknesses of the classical paradigm. Findings - Presents the critique of evolutionary robotics showing how the issues of teleology and autonomy are left unresolved by this paradigm although their solution fits within the proposed framework. Research limitations/implications - The paper highlights the importance of genuine autonomy in the development of artificial cognitive systems. It sets out a framework within which the robofic research of cognitive systems could succeed. Practical implications - There are no immediate practical implications but see research implications. Originality/value - It joins the discussion on the fundamental nature of cognitive systems and emphasise the importance of autonomy and embodiment.

Profiling in sport using momentum and perturbations

Examining a team’s performance from a physical point of view their momentum might indicate unexpected turning points in defeat or success. Physicists describe this value as to require some effort to be started, but also that it is relatively easy to keep it going once a sufficient level is reached (Reed and Hughes, 2006). Unlike football, rugby, handball and many more sports, a regular volleyball match is not limited by time but by points that need to be gathered. Every minute more than one point is won by either one team or the other. That means a series of successive points enlarges the gap between the teams making it more and more difficult to catch up with the leading one. This concept of gathering momentum, or the reverse in a performance, can give the coaches, athletes and sports scientists further insights into winning and losing performances. Momentum investigations also contain dependencies between performances or questions if future performances are reliant upon past streaks. Squash and volleyball share the characteristic of being played up to a certain amount of points. Squash was examined according to the momentum of players by Hughes et al. (2006). The initial aim was to expand normative profiles of elite squash players using momentum graphs of winners and errors to explore ‘turning points’ in a performance. Dynamic systems theory has enabled the definition of perturbations in sports exhibiting rhythms (Hughes et al., 2000; McGarry et al., 2002; Murray et al., 2008), and how players and teams cause these disruptions of rhythm can inform on the way they play, these techniques also contribute to profiling methods. Together with the analysis of one’s own performance it is essential to have an understanding of your oppositions’ tactical strengths and weaknesses. By modelling the oppositions’ performance it is possible to predict certain outcomes and patterns, and therefore intervene or change tactics before the critical incident occurs. The modelling of competitive sport is an informative analytic technique as it directs the attention of the modeller to the critical aspects of data that delineate successful performance (McGarry & Franks, 1996). Using tactical performance profiles to pull out and visualise these critical aspects of performance, players can build justified and sophisticated tactical plans. The area is discussed and reviewed, critically appraising the research completed in this element of Performance Analysis.

L'apport de la théorie des systèmes dynamiques complexes à l'ontologie du droit international dans la crise- Analyse de l'action normative du Conseil de sécurité

Cette thèse est une réflexion originale sur le droit international dans la crise, car elle aborde le droit international grâce à une théorie peu connue en droit, celle des systèmes dynamiques complexes. L’étude du cas particulier de la gestion normative de la crise par le Conseil de sécurité illustre les intérêts de l’utilisation d’une théorie novatrice en droit. La théorie des systèmes dynamiques complexes offre les outils d’une réflexion sur le droit, fondée sur les interactions du droit avec le contexte particulier dans lequel il intervient, la crise, et ses acteurs. La mise en lumière de ces interactions favorise une lecture critique du droit international dans la crise et permet de renouveler l’ontologie de ce droit. Les dynamiques complexes appréhendées et définies par cette théorie sont utiles lorsqu’il s’agit d’expliquer les atouts et les limites de l’action normative du Conseil. Par ailleurs en renouvellant l’ontologie du droit, la théorie des systèmes dynamiques complexes facilite une lecture prospective de l’action normative du Conseil et insiste sur le rôle institutionnel du droit.

Analyzing dynamic intellectual capital: System-based theory and application

This research report presents an application of systems theory to evaluating intellectual capital (IC) as organization's ability for self-renewal. As renewal ability is a dynamic capability of an organization as a whole, rather than a static asset or an atomistic competence of separate individuals within the organization, it needs to be understood systemically. Consequently, renewal ability has to be measured with systemic methods that are based on a thorough conceptual analysis of systemic characteristics of organizations. The aim of this report is to demonstrate the theory and analysis methodology for grasping companies' systemic efficiency and renewal ability. The volume is divided into three parts. The first deals with the theory of organizations as self-renewing systems. In the second part, the principles of quantitative analysis of organizations are laid down. Finally, the detailed mathematics of the renewal indices are presented. We also assert that the indices produced by the analysis are an effective tool for the management and valuation of knowledge-intensive companies.

Introduction to Coding Theory for Flow Equations of Complex Systems Models

The modeling of complex dynamic systems depends on the solution of a differential equations system. Some problems appear because we do not know the mathematical expressions of the said equations. Enough numerical data of the system variables are known. The authors, think that it is very important to establish a code between the different languages to let them codify and decodify information. Coding permits us to reduce the study of some objects to others. Mathematical expressions are used to model certain variables of the system are complex, so it is convenient to define an alphabet code determining the correspondence between these equations and words in the alphabet. In this paper the authors begin with the introduction to the coding and decoding of complex structural systems modeling.

Object transportation by multiple mobile robots controlled by attractor dynamics: theory and implementation

Dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for teams of mobile robots, that must transport a large object and simultaneously avoid collisions with (either static or dynamic) obstacles. Here we demonstrate in simulations and implementations in real robots that it is possible to simplify the architectures presented in previous work and to extend the approach to teams of n robots. The robots have no prior knowledge of the environment. The motion of each robot is controlled by a time series of asymptotical stable states. The attractor dynamics permits the integration of information from various sources in a graded manner. As a result, the robots show a strikingly smooth an stable team behaviour.

Dynamic Criteria: a Longitudinal Analysis of Professional Basketball Players" Outcomes

This paper describes the fluctuations of temporal criteria dynamics in the context of professional sport. Specifically, we try to verify the underlying deterministic patterns in the outcomes of professional basketball players. We use a longitudinal approach based on the analysis of the outcomes of 94 basketball players over ten years, covering practically players" entire career development. Time series were analyzed with techniques derived from nonlinear dynamical systems theory. These techniques analyze the underlying patterns in outcomes without previous shape assumptions (linear or nonlinear). These techniques are capable of detecting an intermediate situation between randomness and determinism, called chaos. So they are very useful for the study of dynamic criteria in organizations. We have found most players (88.30%) have a deterministic pattern in their outcomes, and most cases are chaotic (81.92%). Players with chaotic patterns have higher outcomes than players with linear patterns. Moreover, players with power forward and center positions achieve better results than other players. The high number of chaotic patterns found suggests caution when appraising individual outcomes, when coaches try to find the appropriate combination of players to design a competitive team, and other personnel decisions. Management efforts must be made to assume this uncertainty.