Analysis Of Complex Systems Research Articles

An open source package to perform basic and advanced statistical analysis of turbulence data and other complex systems

We present an open-source package that helps the user to perform a basic statistical analysis of a given turbulence dataset. We believe that this package is useful to the entire turbulence community. It can be used to estimate statistical quantities of turbulence such as the spectral density, turbulence intensity, integral length scale, Taylor microscale, Kolmogorov scale, and dissipation rate as well as velocity increments, structure functions, and their scaling exponents. Different well-known methods available in the literature were selected so that they can be compared. This package also performs an advanced analysis that includes the scale-dependent statistical description of turbulent cascade using the Fokker–Planck equation, consequently leading to the assessment of integral fluctuation theorems. As a precondition for the stochastic process approach, Markovian properties of the turbulent cascade in scale are tested. This is utilized to estimate the drift and diffusion coefficients of the Fokker–Planck equation. The total entropy production for each independent cascade trajectory can be determined using a Fokker–Planck equation. Estimating total entropy production admits a rigorous law of non-equilibrium stochastic thermodynamics, namely, the integral fluctuation theorem, which must be valid if Markov properties hold and the Fokker–Planck equation is correct. This approach to the turbulent cascade process has the potential for a new way to link the statistical description of turbulence, non-equilibrium stochastic thermodynamics, and local turbulent flow structures. Finally, we emphasize that the presented package can be used for the analysis of other data with turbulent-like complexity as well.

Competencies, skills and abilities of managers and staff in the era of the Russian economy digital transformation

The article analyzes the peculiarities of changing the competence profile of employees and managers in modern conditions of digital transformation of economic and other spheres of life. The key branches and directions of digitalisation of the Russian economy, directly or indirectly determining changes in competencies, skills and abilities of personnel and managers, are presented. The article is based on the methodology of complex approach and system analysis. The theoretical basis of the article is the publications of Russian researchers devoted to the problems of digitalisation of the Russian economy. Familiarization with regulatory documents and government programs, methods of comparative analysis are chosen as research methods. The methods used also include the method of expert assessments, normative and logical methods. In a temporary retrospective, the changes and peculiarities of the influence of labor and capital factors on the growth rates of Russia’s gross domestic product are considered separately. In conclusion, the transformation trends in some categories of personnel skills by 2030 are presented, on their basis a conclusion about the competitiveness of a specialist in the future is made. The following information will allow representatives of Russian business and top management of Russian companies to navigate in the established areas of development of the competence profile of personnel and managers, as well as make rational management decisions to create professional teams of employees.

Dispersion heterogeneous recurrence analysis and its use on fault detection

Recurrence plot is an effective tool for portraying system dynamics. However, dealing with distance matrices through the Heaviside function which is difficult to determine the threshold may lead to the loss of much important information, such as information about transitions between states. Therefore, in this paper, we propose a novel dispersion heterogeneous recurrence analysis for complex systems to explore their intrinsic characteristics and structure. The use of dispersion patterns in symbolic dynamics can retain valuable information better than the original defined recurrence plots and avoid the challenge of choosing a threshold. Moreover, we use the iterated function system to provide a visual display of the transition information between patterns. Finally, attention entropy is used to develop a dispersion heterogeneous recurrence quantification analysis. Experimental results show that the method is able to detect the changes of system characteristics with parameters. Also, it can be combined with clustering and classification algorithms for fault detection of railway vehicle systems.

Green innovation and income inequality: A complex system analysis

The objective of this paper is to analyse the relationship between income inequality and environmental innovation. To this end, we use the Economic Fitness and Complexity algorithm to compute an index of green inventive capacity in a panel of 57 countries over the period 1970–2010. The empirical analysis reveals that, on average, inequality is detrimental to countries’ capacity to develop complex green technologies. Using non-parametric methods we further articulate this general finding and uncover interesting non-linearities in the relationship between innovation and inequality.

Algorithm for Optimization of Inverse Problem Modeling in Fuzzy Cognitive Maps

Managerial decision-making is a complex process that has several problems. The more heterogeneous the system, the more immeasurable, non-numerical information it contains. To understand the cognitive processes involved, it is important to describe in detail their components, define the dependencies between components, and apply relevant algorithms for scenario modelling. Fuzzy cognitive maps (FCMs) is the popular approach for modeling a system’s behavior over time and defining its main properties. This work develops a new algorithm for scenario analysis in complex systems represented by FCMs to provide support for decision-making. The algorithm allows researchers to analyze system-development scenarios to obtain the required change to the system’s components that leads to the target state. The problem of determining a system’s initial state is most conspicuous when constructing a compound or unbalanced fuzzy maps. Currently, a brute force algorithm is used to calculate the steps needed to approach a target, but that takes exponential time. The paper describes a new algorithm to obtain the initial values of the controlled concepts in fuzzy cognitive maps using the theory of neutrosophic fuzzy equations. This approach reduces the time needed to find the optimal solution to a problem, and it allows inverse problems to be solved in the fuzzy cognitive maps as a part of the scenario-modeling framework.

How Cooperatively Folding Are Homopolymer Molecular Knots?

Detailed thermodynamic analysis of complex systems with multiple stable configurational states allows for insight into the cooperativity of each individual transition. In this work we derive a heat capacity decomposition comprising contributions from each individual configurational state, which together sum to a baseline heat capacity, and contributions from each state-to-state transition. We apply this analysis framework to a series of replica exchange molecular dynamics simulations of linear and 1-1 coarse-grained homo-oligomer models which fold into stable, configurationally well-defined molecular knots, in order to better understand the parameters leading to stable and cooperative folding of these knots. We find that a stiff harmonic backbone bending angle potential is key to achieving knots with specific 3D structures. Tuning the backbone equilibrium angle in small increments yields a variety of knot topologies, including $3_1$, $5_1$, $7_1$, and $8_{19}$ types. Populations of different knotted states as functions of temperature can also be manipulated by tuning backbone torsion stiffness or by adding side chain beads. We find that sharp total heat capacity peaks for the homo-oligomer knots are largely due to a coil-to-globule transition, rather than a cooperative knotting step. However, in some cases the cooperativity of globule-to-knot and coil-to-globule transitions are comparable, suggesting that highly cooperative folding to knotted structures can be achieved by refining the model parameters or adding sequence specificity.

Order pattern recurrence for the analysis of complex systems

In this paper, order pattern recurrence plot (OPRP) and order pattern recurrence quantification analysis (OPRQA) are proposed to quantify recurrence characteristics of complex systems. The method uses the recurrence of order patterns in symbolic sequence to explore the order structure of the original data, in which the color of the symbol is employed to distinguish different order patterns. The main advantage of the approach is its robustness with respect to non-stationary data and low requirements for the length of the required time series. The method is demonstrated to be effective in synthetic data and real data. As demonstrated in simulation models, the conclusion is that the method can not only make a distinction between chaotic system and random noise but also quantify various bifurcation transition scenarios like period doubling or other phenomena associated with chaos-to-chaos transitions in logistic map. In empirical analysis, this approach helps observe the different performance of the time series before, during and after the financial crisis. In addition, differences of stocks between developing countries and developed countries are reflected in OPRP and quantified by the corresponding OPRQA. The proposed method brings together recurrence plots and symbolic dynamics to empower researchers with effective means to visualize and quantify complex behavior in dynamic system.

Axiomatic design for lean autonomous maintenance system: an application from textile industry

PurposeAutonomous maintenance (AM), one of the pillars of total productive maintenance (TPM), aims to achieve performance toward zero defects and zero breakdowns. AM system equipped with comprehensive lean tools provides continuous improvement during the AM activities. Despite its long duration, establishing a lean AM system with a robust guideline would provide significant benefits such as high quality and short lead time. Therefore, AM design approach should be provided in a holistic and detailed manner. This study aims to develop a framework for AM design, including preliminary, reactive, preventive and proactive steps using the axiomatic design (AD).Design/methodology/approachRequirements and technical parameters of the AM system are explored with AD. An extensive literature review and a real-life application are presented.FindingsThe proposed design was validated by adapting the proposed roadmap to a textile manufacturing system in Turkey. The application results justify the established AM system design with an average downtime improvement of 69.2% and the average elapsed time between two failures improvement of 65.1% for apparel department.Originality/valueThis study has the novelty of establishing an overall AM system design with all of its stages stepwise. It presents a comprehensive guideline in terms of integration of lean philosophy into AM design by generating maintenance-related use cases for lean tools. The developed approach facilitates creating and analyzing complex systems to improve maintenance implementations while reducing nonvalue-added operations.

Research progress in theory and green analytical application of chemical multi-way calibration

<p indent="0mm">The combination of chemical multi-way calibration and modern high-order instruments for accurate quantitative analysis in complex systems has a unique “second-order or higher-order advantage”. This analytical strategy meets the development needs of green analytical chemistry, and has been widely used in the fields of biology, medicine, food, environment, <italic>etc</italic>. This review introduces the latest research progress in theories and applications of chemical multi-way calibration, and the contribution of multi-way calibration methods to green analytical chemistry is emphasized. In the theory part, we focus on the multilinear models and their extensions, multi-way calibration algorithms with second-order or higher-order advantages, and some key issues in the use of multi-way calibration methods. In the application part, the representative applications of different high-order analytical instruments coupled with second-, third-, and fourth-order calibration methods in the past five years are systematically reviewed.

Формирование системы безопасности персонала строительных фирм с использованием математического моделирования рисков

The need for an efficient assessment of the occupational risk of the employees involved in the construction of buildings and structures was established. A study was conducted for substantiating the system for ensuring the safety of personnel in the construction complex using quantitative risk criteria developed based on of mathematical modeling. Technological processes at the construction sites and in the organizations are considered. The methods of complex (integral) system analysis, process analysis, aggregation and optimization of risk parameters were also applied. Based on the systematic studies of the technological processes at facilities under construction, a methodology for assessing occupational risk was developed. The ways and means of achieving the strategic goal of the occupational safety, which is to ensure the safe professional activity of personnel, are considered. The possibility of forming a set of criteria for the quantitative assessment of occupational risk based on the mathematical modeling is shown. The key to obtaining efficient evaluative expressions is the use of real statistical data in the numerical form. The importance is noted considering the interaction of various harmful and hazardous production factors that affect personnel and are formed according to the principle of systems emergence. The developed criteria for the quantitative assessment of occupational risk are an objective and reliable basis for the development of an efficient system for ensuring the safety of construction employees. The described technique is based on the fundamental provisions of the physical and mathematical theory, the scientific discipline «Life Safety», the theory of prognostic and experimental research. It can be used to develop measures for creating a safe working environment in all the industries.

Crisis and society: developing the theory of crisis in the context of COVID-19

The theory of crisis and society is advanced by developing a complex systems analysis and is applied to the COVID-19 pandemic. Five issues are identified, discussed and resolved: the definition of crisis; whether a crisis is treated as real or as a socially constructed narrative, or both; the underlying concept and theory of society and its alternative forms; and the different kinds of change in relationship between crisis and society (recuperation, intensification, transformation and catastrophe). This complex systems approach to crisis is applied to the COVID-19 pandemic, analysing the cascade of the crisis through institutional domains and the consequent changes to multiple regimes of inequality.

Numerical Simulations of the Flow Dynamics in a Tube with Inclined Fins Using Open-Source Software

Finned tubes increase the convective heat transfer in heat exchangers, reducing the total energy consumption of integrated industrial processes. Due to its stability and robustness, Computational Fluid Dynamics (CFD) commercial software is generally utilized for analyzing complex systems; however, its licensing is expensive. Nowadays, open-source software is a viable substitute for proprietary software. This work presents a CFD analysis of the hydrodynamics of a finned tube using the OpenFOAM and SALOME Meca platforms. The results are compared with experimental data and CFD using the commercial software Fluent, both previously reported in the open literature. This work studies the fluid flow pattern around a tube with six 45-degree-angled fins, and the working fluid, air, is considered as an incompressible fluid. Special attention is paid to calculating the pressure coefficient distribution for the internal and external surfaces of the inclined fins. Open-source platforms allow researchers to visualize how the airflow interacts with the cylinder and the fin surfaces to form a fluid structure, formerly known as a horseshoe vortex system. The findings of the analysis of flow dynamics in the channel between inclined fins and in the wake help explain the results obtained in experimental tests and are relevant for the configuration of a bank of tubes with inclined fins.

Identification of Communities With Multi-Semantics via Bayesian Generative Model

Discovering communities is an essential step in the analysis of complex systems, and it has two purposes: to identify functional modules and to interpret semantics. However, most of the existing community detection methods only focused on identify communities, while learning the semantics interpretation of communities has not been fully studied. In this paper, we focused on the problem of identifying communities and learning the semantics interpretation of modules jointly in an end-to-end model. We designed a novel generative model which combines two closely related parts, one for community discovery and the other for content clustering and semantics interpretation. By extracting the potential correlation between these two parts, our new method is not only robust to discovering communities, but also able to provide a community with more than one semantic topic. As for model inference, we developed a variational algorithm from a Bayesian point of view. Experimental results on the artificial benchmark and real networks showed the superior performance of the proposed approach over existing methods in terms of effectiveness and efficiency. We also analyzed semantic interpretability of community detection results through a case study over a large-scale music platform dataset.

Computational Experiments for Complex Social Systems—Part II: The Evaluation of Computational Models

Computational experiments are an important method for carrying out the quantitative analysis of complex systems and play a major role in mapping the real world to the virtual world. However, the flexibility of computational experiments leads to arbitrary modeling processes and unconvincing results, which greatly hinder the large-scale application of this method. In this context, the verification of computational models has become an urgent problem in this field. Currently, model evaluation is still in its infancy and the existing evaluation methods are not mature enough. Thus, we took epidemic models as the research object and proposed a capability maturity evaluation framework for computational models of artificial society. The framework differs from previous assessment methods that focus on the validity of results, but instead provides a comprehensive evaluation from two perspectives: 1) evaluation of the model itself—by comparing the expectation with the final implementation, we can obtain whether the model meets the expectation and 2) comparison between different models—by evaluating the implementation process of each model and comparing the results, we can identify more mature models. The implementation of the model is evaluated from input, process, and output. Further, specific analyses and evaluations are conducted for several representative COVID-19 models to verify the validity of this evaluation framework. The results of the case study show that the proposed evaluation framework can help decision-makers identify more mature and referential models, and point out the directions where modelers can improve their models.

Some Properties of Fractional Cumulative Residual Entropy and Fractional Conditional Cumulative Residual Entropy

Fractional cumulative residual entropy is a powerful tool for the analysis of complex systems. In this paper, we first provide some properties of fractional cumulative residual entropy (FCRE). Secondly, we generate cumulative residual entropy (CRE) to the case of conditional entropy, named fractional conditional cumulative residual entropy (FCCRE), and introduce some properties. Then, we verify the validity of these properties with randomly generated sequences that follow different distributions. Moreover, we give the definition of empirical fractional conditional accumulative residual entropy and prove that it can be used to approximate FCCRE. Finally, the empirical analysis of the aero-engine gas path data is carried out. The results show that FCRE and FCCRE can effectively capture complex information in the gas path system.

Design of experiment techniques for the optimization of chromatographic analysis conditions: A review.

Design of experiment (DoE) techniques have been widely used in the field of chromatographic parameters optimization as a valuable tool. A systematic literature review of the available DoE techniques applied to the development of a chromatographic analysis method is presented in this paper. First, the most common available designs and the implementation steps of DoE are comprehensively introduced. Then the studies in recent 10 years for the application of DoE techniques in various chromatographic techniques are discussed, such as capillary electrophoresis, liquid chromatography, gas chromatography, thin-layer chromatography, and high-speed countercurrent chromatography. Current problems and future outlooks are finally given to provide a certain inspiration of research in the application of DoE techniques to the different chromatographic techniques field. This review contributes to a better understanding of the DoE techniques for the efficient optimization of chromatographic analysis conditions, especially for the analysis of complex systems, such as multicomponent drugs and natural products.

Foundations and Applications of Information Systems Dynamics

Although numerous advances have been made in information technology in the past decades, there is still a lack of progress in information systems dynamics (ISD), owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems. The value of ISD lies in its ability to guide the design, development, application, and evaluation of large-scale information system-of-systems (SoSs), just as mechanical dynamics theories guide mechanical systems engineering. This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space, improving a mathematical theory for information measurement, and proposing a dynamic configuration model for information systems. In this way, it establishes a basic theoretical framework for ISD. The proposed theoretical methodologies have been successfully applied and verified in the Smart Court SoSs Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization. The proposed ISD provides an innovative paradigm for the analysis, design, development, and evaluation of large-scale complex information systems, such as electronic government and smart cities.

Application of integrated STAMP-BN in safety analysis of subsea blowout preventer

Blowout preventer (BOP) plays a key role in preventing blowout accidents from occurring during offshore or deepwater drilling. The safety of BOP is affected by diverse components and interactions among them. It is vital to identify the crucial failure modes using safety assessment method. To perform a qualitative, quantitative, and systematic safety assessment of BOP, this paper presents an integrated method—using the system-theoretic accident model and process (STAMP)-Bayesian network (BN)—for evaluation of the structure safety and prediction of the failure scenarios. In the proposed method, STAMP is used to identify the failure scenarios by establishing a hierarchical control and feedback model that tallies with the BOP structure, while BN is adopted to calculate the probabilities of potential failure modes based on the outcomes of STAMP. The approach is then explored in a case study where factors regarding humans, components and control systems, and constraints and control relationships among them are all considered. The results demonstrate the feasibility of the integrated method as a way of performing a safety analysis for BOP. This research overcomes the deficiencies of traditional methods that cannot effectively evaluate the interactions of components, thereby providing a reference for safety/risk analyses of complex systems.

Measures of Administrative Coercion in the Field of Taxes and Fees in Ukraine

Based on the methodology of complex system analysis, measures of administrative coercion in the field of taxes and fees in Ukraine are considered. It is noted that estimates of administrative coercion have a universal character. Types of administrative coercion are analyzed: measures of administrative suspension, measures of administrative recovery, measures of administrative and procedural support, measures of administrative enforcement in the field of taxes and fees. The content, task, purpose, grounds and procedure for applying various measures of administrative coercion are defined. The principles of administrative responsibility in taxes and fees are considered. Different aspects of administrative appeals and appeals in the administrative-jurisdictional process and administrative proceedings of decisions, resolutions and judgements regarding administrative offences in the field of taxes and fees in Ukraine are disclosed. The trends in the application of administrative coercion measures are characterized. It is proposed to solve problematic issues regarding measures of administrative coercion in tax law on the basis of codification, unification and systematization of these measures, which will significantly strengthen the protection of rights and legitimate interests of tax and fee payers, tax agents, and banking institutions in Ukraine.

Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number and Information Entropy.

To promote the application of entropy concepts in uncertainty analysis of water resources complex system, a quantitative evaluation and obstacle factor diagnosis model of agricultural drought disaster risk was proposed using connection number and information entropy. The results applied to Suzhou City showed that the agricultural drought disaster risks in Suzhou during 2007–2017 were all in middle-risk status, while it presented a decreasing trend from 2010. The information entropy values of the difference degree item bI were markedly lower than those of the difference degree b, indicating that bI provided more information in the evaluation process. Furthermore, the status of drought damage sensitivity and drought hazard were improved significantly. Nevertheless, high exposure to drought and weak drought resistance capacity seriously impeded the reduction of risk. Thus, the key to decreasing risk was to maintain the level of damage sensitivity, while the difficulties were to reduce exposure and enhance resistance. In addition, the percentage of the agricultural population, population density, and percentage of effective irrigation area were the main obstacle factors of risk and also the key points of risk control in Suzhou. In short, the results suggest that the evaluation and diagnosis method is effective and conducive to regional drought disaster risk management.