Complex Systems Research Research Articles

Complex relationships among firm risk, asymmetric volatility, volatility skew, and the leverage effect

In finance, the asymmetric volatility phenomenon (AVP) and volatility skew are two well‐known topics related to firm risk. In early research, the AVP was documented by Black (Proc 1976 Meetings Business Econ Stat Sect 1976, 177–181), who proposed two possible explanations. The veracity of one such explanation, the “leverage effect,” has long remained controversial. The volatility skew is considered to represent collective phenomena caused by heterogeneous beliefs regarding firm risk among investors. Although the relationship between leverage and firm size has been investigated, the investigations have yielded inconsistent conclusions. All related empirical evidence indicates that the relationships among firm risk, asymmetric volatility, volatility skew, and the leverage effect are complex. Regarding accounting principles, Ryan (Account Horizons 1997, 11, 85–95) proposed two concepts for describing firm risk. One of those concepts, “sources of operating risk versus leverage,” revealed the key to linking firm risk to leverage. Among the multidisciplinary methodologies, cybernetics plays a crucial role in complex systems research. The causal nets and feedback loop analysis of cybernetics offer accurate descriptions of realities in terms of causality, nonlinearity, and temporality. This study uses cybernetics to connect the accounting risk concept in microlevel analysis to volatility changes in macrolevel phenomena. This not only validates interdisciplinary analysis with different evidence but also enables the development of a managerial interpretation of different states of firm risk. This study contributes a novel approach that involves the application of a microlevel concept to macrolevel analysis and evidences the “less is more” art of modeling complex phenomena (Schuster, Complexity 2005, 11, 11–13). © 2016 Wiley Periodicals, Inc. Complexity 21: 329–341, 2016

Survivability of Deterministic Dynamical Systems.

The notion of a part of phase space containing desired (or allowed) states of a dynamical system is important in a wide range of complex systems research. It has been called the safe operating space, the viability kernel or the sunny region. In this paper we define the notion of survivability: Given a random initial condition, what is the likelihood that the transient behaviour of a deterministic system does not leave a region of desirable states. We demonstrate the utility of this novel stability measure by considering models from climate science, neuronal networks and power grids. We also show that a semi-analytic lower bound for the survivability of linear systems allows a numerically very efficient survivability analysis in realistic models of power grids. Our numerical and semi-analytic work underlines that the type of stability measured by survivability is not captured by common asymptotic stability measures.

Education's Complexity in the Context of Human Development

Claiming to be a complex approach, the updated worldwide Sustainable Development Goals agreement broadens its educational scope and acknowledges the integrated and indivisible character of human development through diverse dimensions. Complex systems research provides ways to improve our understanding of the complexity of education and to explore how education fits within the context of human development. To account for ‘effect‐based’ research on education complexity, using the American Community Survey data, we developed a model by inferring a probabilistic network structure of diverse aspects of human development dimensions including education. We explored the model by network analysis methods to discover the intrinsic relationships among education variables and the extrinsic relationships of education with other dimensions of human development in the USA. The results confirmed the well‐known rationale of the relationship between education and wealth, and expanded the understanding of complexity of education as it is part of the life course (timing of individual development) and of the cultural construction of identity. Copyright © 2016 John Wiley & Sons, Ltd.

Application of optimal data-based binning method to spatial analysis of ecological datasets

Investigation of highly structured datasets to unveil statistical regularities is of major importance in complex system research. The first step is to choose the scale at which to observe the process, the most informative scale being the one that includes the important features while disregarding noisy details in the data. In the investigation of spatial patterns, the optimal scale defines the optimal bin size of the histogram in which to visualize the empirical density of the pattern. In this paper we investigate a method proposed recently by K.H. Knuth to find the optimal bin size of an histogram as a tool for statistical analysis of spatial point processes. We test it through numerical simulations on various spatial processes which are of interest in ecology. We show that Knuth optimal bin size rule reducing noisy fluctuations performs better than standard kernel methods to infer the intensity of the underlying process. Moreover it can be used to highlight relevant spatial characteristics of the underlying distribution such as space anisotropy and clusterization. We apply these findings to analyse cluster-like structures in plants’ arrangement of Barro Colorado Island rainforest.

Research on the method of the Test and Evaluate (T&E) of Complex Simulation System

With the development of science and evolution of society, the structure of a system becomes more and more complicated. There is an increasing need for the research, development and application of complex systems. Based on the brief introduction to the significance of T&E, the relationship between T&E and development status in the domestic and overseas, expounding the part of the establishment of the theory and methodology of T&E at the technical and methodological level, which offers references for the further development of the test and evaluation method and technology of T&E of complex systems.

Immunity of multiplex networks via acquaintance vaccination

How to find the effective approach of immunizing a population is one open question in the research of complex systems. Up to now, there have been a great number of works focusing on the efficiency of various immunization strategies. However, the majority of these existing achievements are limited to isolated networks, how immunization affects disease spreading in multiplex networks seems to need further exploration. In this letter, we explore the impact of the acquaintance immunization in multiplex networks, where two kinds of immunization strategies, multiplex node-based acquaintance immunization and layer node-based acquaintance immunization, are proposed. With the generating function method, our theoretical framework is able to accurately calculate the critical immunization threshold which is one of the most important indexes to predict the epidemic regime. Moreover, we further uncover that, with the increment of degree correlation between network layers, the immunization threshold declines for multiplex node-based acquaintance immunization, but slowly increases for layer node-based acquaintance immunization.

An initial categorization of foundational research in complex technical systems

There has been intense foundational research in complex technical systems (CTSs) over the last half century. These systems are exemplified by advanced mechatronics systems, embedded control systems, real-time systems, agent-based smart systems, distributed software systems, internet of things systems, and cyber-physical systems. The objective of this paper is to offer an initial cataloguing of the various research domains and to identify the major research issues. The paper has an ontological flavour, because it concentrates on what research has been and is being done, rather than on why and how research is done. The underpinning study has been done in three stages: (i) intuition-driven exploration of a reference set of related academic publications, (ii) evidence-based specification of a categorization of the domains and subdomains of research, and (iii) refinement and validation of the proposed classification based on a control set of related academic publications. The proposed reasoning model identifies three categories of research domains. The ‘intellectualizations’ category includes research domains such as: (i) philosophy, (ii) ontology, and (iii) epistemology of CTSs. The research domains included in the ‘realizations’ category are: (iv) methodology, and (v) creation of CTSs. The domains considered in the ‘influences’ category are: (vi) manifestations, and (vii) axiology of CTSs. Based on the proposed reasoning model a landscape of foundational research in CTSs is proposed for public debate. Our follow-up study focuses on the extension of the proposed classification to other families of complex engineered systems such as sociotechnical systems and social ecosystems.

Introducing Change into Complex Cognitive Work Systems

Change in a complex system—for example, to its technology, procedures, or information flows— no matter how small, has the potential to create large effects and ripples of disruption. A complex system’s dynamics cannot be fully known, and the effects and disruptions produced by change are difficult to predict. Nonetheless, complex systems can be at least partly understood in terms of patterns in their dynamics, generalizable principles, and mechanisms of control, balance, and adaptation. This panel will focus on complex systems research and what they suggest about how to introduce change into a complex system such that the work system resilience and health are disrupted minimally. Case studies may be discussed, as well; examples of changes to established complex work systems. These changes include introducing remotely piloted aircraft systems (RPAS) into the National Airspace System (NAS), additional automation into air traffic control, and new technology into military air combat training.

Calculation and research of contact ophthalmic dual application lenses

Subject of research. Algorithm for calculation of contact ophthalmic lenses for dual application has been suggested based on unified approach for their calculation. The algorithm has been tested on the composition of Goldmann ophthalmic lenses and Panfundoscope lens optical systems. Method. The condition of mutual unambiguous orientation of patient’s eye and instruments is performed at the initial calculation step by face mounting and movement of coordinate table with optical head. Then such type of patient's eye optical system model is selected that the lens would be combined with the front surface of eye cornea optical system. Pupil of patient eye is under anesthesia. At the final calculation step we determine the functions of optical lens image quality and their values based on medical and technical requirements for the components of the complex system. Main results. The algorithm for ophthalmic lenses calculation has been suggested and its correctness has been proved practically on the example of two basic models in the group of such type lenses being applied in practice as a part of complex system with ophthalmic laser coagulators. Optical calculation of Goldmann ophthalmic contact lenses and Panfundoscope is presented. The method of neutralization is optimal for Goldmann lenses. The first component in Panfundoscope operates the position of object planes whereas the second component operates the position of complex system with ophthalmocoagulator's pupils. Computer modeling of complex system "Computer model of eye-ophthalmic lens" in ZEMAX confirmed the correctness of calculation algorithm in which the criteria of diffraction image quality has been used. Application possibility of simplified computer eye model called "Reduced eye" by Verbitskiy has been demonstrated. Practical relevance. The general scientific approach to the problem of synthesis, calculation and research of complex system with contact ophthalmic lenses for diagnostics and laser intervention on the eyeground has been found and confirmed. The results obtained have practical significance for the further development of optical calculation method and optical ophthalmologic instruments such as the fundus camera, wavefront analysers, opthalmoscopes and systems of vision optical correction.

Importance of randomness in biological networks: A random matrix analysis

Random matrix theory, initially proposed to understand the complex interactions in nuclear spectra, has demonstrated its success in diverse domains of science ranging from quantum chaos to galaxies. We demonstrate the applicability of random matrix theory for networks by providing a new dimension to complex systems research. We show that in spite of huge differences these interaction networks, representing real-world systems, posses from random matrix models, the spectral properties of the underlying matrices of these networks follow random matrix theory bringing them into the same universality class. We further demonstrate the importance of randomness in interactions for deducing crucial properties of the underlying system. This paper provides an overview of the importance of random matrix framework in complex systems research with biological systems as examples.

Emergent computation of complex systems: a comprehensive review

Emergent computation is proposed in the study of self-organisation, collective and cooperative behaviour and it has become an important approach to complex system research with further development of the complexity science. From the perspective of complexity study, this paper reviews and analyses the emergent computation of complex systems, which is intended to deepen the understanding of the mechanism for emergence phenomenon and grasp the development directions of complexity study. At first, the concept, models and research methods of emergent computation are introduced and stated. Furthermore, the layout design problems in complex engineering systems and the collective behaviour issues in complex social systems are chosen as representatives to expand the review. The generation mechanisms of emergent computation in engineering systems are expounded and the emergent computation models of collective behaviour which include synchronisation and public opinion propagation are discussed. Based on the review of research status, further analysis on the existed problems and shortcomings is made and some perspectives on the development trends of future research which relate to emergent computation of complex systems are provided.

Emerging from crisis with new approaches to science of society

The recurrence of economic crises serves to illustrate the limits of neoclassical economics and the contemporary established models. Modern–day economic developments are highly influenced by the theory of complexity. In terms of thermodynamics, the inputs of the process consists in economically valuable natural resources and the outputs are worthless wastes; the matter–energy is absorbed in the economic process in a low entropy state which in turn is eliminated in a state of high entropy. Consequently, an updated methodology is required as all activities and overall economic processes demonstrate the inevitably entropic processes. Complex systems research represents the viable alternative for sustainable growth in the following decades. The concept of emergence represents an insightful argument against the well–planned and ordered nature of the social sciences universe. The study of complex systems, evolutionary economics and interdisciplinary research offers the possibility of new developments.

Operational and exchange properties of systems research problems

In article, on the example of the tasks arising at research of products properties, created at the enterprises of a military-industrial complex, problems of operational and ex-change properties of complex technical systems research are investigated. Operational properties of systems characterize results (effects) of activity with use of systems (op-erational properties, in particular, are efficiency of system functioning for achievement of the given objective, system potential, system capabilities). Exchange properties characterize properties of exchange of results of activity (exchange properties, in par-ticular, are competitiveness of a product, competitiveness of the enterprise). As shown, it is expedient to study exchange properties of systems using the concept and method-ology of estimation of operational properties of systems. Indicators for operational properties estimation proposed and on their basis indicators for exchange properties of the systems suggested. Indicators suggested in such a way that their estimation suppose usage of mathematical models. This gives the chance to solve a range of research prob-lems of operational and exchange properties of systems. Need of definition of concept is proved, and then the concept of model of a research problem proposed. The direc-tions of research problems models usage for automation of the solution of operational and exchange properties research problems discussed.

Researches and Applications of Computational Experiments

Computational experiments are emerging computational methods for complex system research, which have drawn wide attentions from both domestic and foreign scholars. The rapid growth of computational experiments shows great application potential in research domains related to control and management of complex systems, such as social security, e-commerce, financial markets and so on. In this paper, we will firstly introduce the basic idea of computational experiments and review the research foundations of computational experiments including experimental design and computational simulation. Then we will mainly focus on presenting the main research contents of computational experiments including construction of models, design of computational experiments, and execution of computational experiments. Finally, we will discuss the applications and the existing problems in this field and present several potential research directions.

P395: Switching from bimanual to unimanual tapping reveals two distinct post-switching beta synchronization processes

P395: Switching from bimanual to unimanual tapping reveals two distinct post-switching beta synchronization processes

O10: Effect size of quantitative muscle imaging in Duchenne muscular dystrophy exceeds the effect size of clinical scores of muscle function

s of Oral Presentations / Clinical Neurophysiology 125, Supplement 1 (2014) S1–S339 S31 confirmed Duchenne muscular dystrophy. Physical assessment was performed using the motor function measurement (MFM) scale. Quantitative magnet resonance imaging (qMRI) of thigh muscles was performed using the two-point Dixon method. One year functional and imaging changes were different according to the age and walking abilities at inclusion (group 1: below the age of seven; group 2: seven years and older and ambulant; group 3: non-ambulant). While patients of the first group still showed improvement of motor abilities, in group 2 the largest effect size (1.2) was found in the D1 subscore (standing and transfer function) of the MFM, and in group 3 the largest effect size was found for the total MFM score (0.66). In contrast, the effect sizes using qMRI was much larger consisting of 1.6 in group 1 (all thigh muscles), 4.1 in group 2 (hamstrings), and 2.3 in group 3 (knee extensors). These data suggest that qMRI has an added value compared to clinical outcome measures when designing therapeutic clinical trials in patients with DMD. Power analysis suggest that there are only a few needed patients to show an effect of a putative novel treatment when using quantitive muscle MRI in DMD. O11 Estimation of the muscle fiber density from the motor unit action potential I. Goker1, T. Artug2, O. Osman2, B. Baslo3 1Istanbul Arel University, Biomedical Engineering, Istanbul, Turkey; 2Istanbul Arel University, Electrical and Electronics Engineering, Istanbul, Turkey; 3Istanbul University, Medical Faculty, Istanbul, Turkey Introduction: The aim of this study is the estimation of the muscle fiber density (FD) from the Motor Unit Action Potentials (MUAP) to form a method for monitoring the progress of neuromuscular diseases. Methods: Data groups representing motor units of neurogenic (n=5), myopathic (n=5) and healthy cases (n=5) were created via EMG Simulator v3.6. MUAPs generated from each data group have been detected through a concentric needle electrode of a scanning EMG system. The spikes of the single fiber action potentials within the MUAPs have been found by computing the second-order derivative of MUAPs to estimate the detected number of fibers. MUAPs from 20 different locations within a Motor Unit Territory (MUT) have been acquired. The fiber density (FD) has been computed by taking the average of these numbers of fibers. True FDs have been computed for each MUT. Mean Square Errors (MSE) have been computed for each data group to determine the sensitivity of the method. Results: The test statistics of the FDs (mean ± SD) have been found as 4.13±1.31 (Min: 2 and Max: 8), 2.37±0.98 (Min: 1 and Max: 5) and, 2.40±0.70 (Min: 1 and Max: 4) for neurogenic, myopathic and healthy cases respectively. Mean true fiber densities have been 5.66, 2.57 and 1.50 and MSE have been 4.02, 0.15 and, 0.86 for neurogenic, myopathic and healthy cases respectively. These MSE values have been suggested that this method is more selective for myopathic cases compared to neurogenic and healthy cases. Conclusion: Computation of FD via the second-order derivative of MUAPs can be considered as a beneficial preliminary research. Nevertheless, this method might be extended by taking into account other variables such as maximum amplitude to increase the sensitivity for neurogenic cases.

Communication in Multidisciplinary Systems Architecting

Systems architecting is multidisciplinary by nature. It is interesting to note that the methods and tools that are developed and presented in literature are mostly based on one or a very limited number of formalisms. This means that an often large part of the stakeholders involved in the architecting process are hindered in the understanding of, and contributing to the architecture.The paper investigates the architecting process and complexity in combination with knowledge and knowledge creation. Communication is identified as essential. It thus follows that tools that base on one formalism limit this communication in a multidisciplinary setting. Based on experiences from architects, literature and the author, ingredients for successful multidisciplinary architecting are listed, and directions for future research in complex systems architecting are given, based on these ingredients.

SoS Benefiting from Complex Systems Research

System of Systems (SoS) projects and system development are generally considered to be complex. Although there is no generally agreed definition of complexity, the aspects of autonomy and independence of the included systems are generally considered to be the key aspects driving complexity.However SoS projects and systems do not heavily draw on the development of complex systems principles from literature developed more broadly. While working outside the Ashby space of requisite variety is recognized, notions of being on the edge of chaos are not generally recognized as leading to more innovative solutions. Operating in the Paretian space of power laws, with fractal and scaling principles, rather than operating under Gaussian statistics, also receives scant attention. Self-organized criticality and the role of tiny initiating events is not dwelt on. Recognition that natural and business systems undergo cycles, which usually involves changing stability levels, is seldom discussed. Systemic and cascading risk and black swan events are only discussed a little. Sense making and common meaning and the role of attractor cages and path history is normally not made use of. Finally the role of systems intelligence is examined. The benefits of addressing these concepts in system of systems is examined:

Application of System Dynamics to Water Security Research

Water security is an important component of regional security and sustainable development and it significantly affects regional development strategies. Flood security, water resource security, and water environment security are the basic elements of a water security system. These elements exhibit dynamic and complex characteristics. System dynamics (SD) is a qualitative and quantitative simulation and analysis method for system integration. SD is applicable to complex system research and has achieved significant results in water security system research. This study initially collected literature on water security research and application in recent years, and then verified the progress and deficiencies in current research. Our research on water security focuses on managing and predicating a single subsystem. Our research on flood control and disaster mitigation focuses on managing and forecasting floods. Our research on water resource security focuses on water resource management, carrying capacity, and planning, as well as on sustainable water utilization. Finally, our research on water environment security includes water quality management, water pollution control, early warning systems, and water ecology. The SD method can properly solve the complicated relations in a water security system but exhibits limitations in the following aspects: research on large systems; influence of social environment changes; uncertainties in water security; and the methods, means, and influence of natural environment changes on water security.

Scaling Behavior and Phase Change in Complex Network

Scaling behavior is a extremely typical phenomenon in complex system research, as well as it can act that many Macro indicators in system or distribution function of some variables meet exactly power-law behavior, which possesses different kinds of Exponents. In this article, according to Phase Change concept in Physics, it is researched that the nature in critical state of complex network with Seepage model, and it is totally stated that the basic reason of Self-similar behavior, Fractal behavior, and so on, and also Phase Change in complex network in critical state of complex network in accord with power-law distribution. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3529