Idea Of Self-organization Research Articles

The idea of self-organisation in biology and its critics

The idea of self-organisation in biology and its critics Using the example of Alan Turing's paper on morphogenesis, Ute Deichmann at Ben-Gurion University of the Negev explores self-organisation in biology. The availability of large amounts of genomic and other data and the complexity of biological systems have led to increasing collaboration of biologists with mathematicians and computer scientists. However, the use of mathematics in biology differs from that in physics, and problems arise when basic biological principles, such as the genomic control of basic life processes or the specificity of organisms and their biochemistry, are disregarded. I exemplify the importance of mathematics in biology and the problems this can entail, using the example of mathematician and computer scientist Alan Turing's work on morphogenesis, that is, the generation of form in development.

Позитивная правовая неопределенность как технико-юридический способ изложения права

Introduction. In modern Russian society with high rates of development of market relations, digitalization of the main spheres of life, popularization of the ideas of self-organization and self-regulation, legal uncertainty acts as a bipolar phenomenon, which is not only a consequence of law-making errors, but an effective technical and legal way of presenting regulations. Theoretical analysis. The historical analysis of the formation and development of ideas of certainty and uncertainty in jurisprudence showed that these categories are considered as universal phenomena characteristic of any matter. It was established that absolute certainty is unattainable and not always in demand, while legal uncertainty is inherent in the very nature of law. Еmpirical analysis. It was revealed that the need to ensure mobility and flexibility of legal regulation imposes the task of a reasonable use of legal uncertainty as a technical and legal way of presenting law on the law-making subject, which is reflected in the current legislation. Results. Legal uncertainty is an objective and inevitable phenomenon, and the total regulation of social relations is not always justified. The law is being improved on the basis of the principle of transition from the casuistic to the abstract, which proves its universality.

Learning to Share - Teaching the Impact of Flexible Task Allocation in Human-cobot Teams

Collaborative robots (cobots) are vital for agile concepts of industrial manufacturing and regarded as flexible and low-cost automation solutions. Therefore, learning factory concepts increasingly include handling with cobot technology, their industrial applications and safety concepts. In addition to these fields of knowledge, it is widely considered that work organization at the manufacturing shop floor must be rethought to use the full potential of cobot flexibility. One of the approaches is the flexible task allocation in human-cobot teams. Based on the idea of self-organization, human and cobot tasks are adaptively assessed and optimized. The implementation of this concept enables productivity gains and at the same time reduces negative aspects of automation such as reduced readiness to take action and monotonous work. As this approach requires technological and organizational preconditions as well as prior knowledge of the industrial engineering domain, the paper presents a hands-on educational concept for flexible task allocation in human-cobot teams. Upon an analysis of required competencies and an identification of deficits in existing teaching approaches - based on evaluation criteria such as innovation content, human-cobot team suitability, industrial relevance and reusability - a teaching concept in addition to three hands-on demonstrators was developed. The demonstrators were implemented at the TU Wien Pilot Factory Industry 4.0 allowing for representative task allocation patterns applied in industrial settings. Besides professional educational purposes, the demonstrators can be used for exhibitions as they allow hands-on experiences for the public and therefore contribute to a more realistic perception of the potential, the challenges, and the impact of robots in the manufacturing domain. Thus, working with and evaluating the demonstrators hands-on, not only students and professionals, but also children, teenagers and the general public are able to explore the potential benefits, consequences and necessary preconditions within potential use cases.

Сравнительный анализ принципа эволюции классической и неклассической науки

The relevance of the study of the mechanism of evolution is determined by the fact that the understanding of scientific laws is changing in modern science. From the microworld to the megaworld, the historical nature of the processes occurring in them is recognized, which should be reflected in the interpretation of laws. The author sets out to reveal the prerequisites of the idea of self-organization, which is a distinctive feature of evolutionary processes in the synergetic picture of the world of post-non-classical science. The idea of self-organization grows out of the concepts of evolution developed in the classical and non-classical periods of the development of modern science. The article is devoted to a comparative analysis of the concepts of the evolution of these periods. The dominant approach in the modern philosophy of science is the history of science, so the author is guided by the methodology of historical and scientific research, when comparative analysis is implemented through finding out the similarities and differences of the stages of interest. The article substantiates the thesis that at this stage the concept of evolutionism is based on the recognition of the time parameter either in the form of an infinite sequence of events embodied in the present («external time»), or in the form of the principle of historicity («internal time»). The classical concept of evolution was a hypothesis. In non-classical science, the concept of evolution receives a scientific — empirical and theoretical — justification. To specify the principle of evolution in this period, the material from astrophysics, biology and historical science is given. The novelty of the obtained results is connected with the recognition of the hypothetical nature of the idea of evolution in the non-major non-rationalist branch of descriptive natural science of classical stage, the acquisition of scientific justification by it (the idea of evolution) at the non-classical stage, as well as with the transition from the concept of «external» to «internal» time. «Internal» time is the essence of the new concept of historicism, where evolution is interpreted as self-organization. A new concept of evolution and a new type of scientific laws set the prospect for further research. Key words: the concept of evolution, classical / non-classical science, time, the principle of historicism, V. I. Vernadsky, M. Foucault, sciences of inorganic / organic nature, historical science.

Expression of ideas of self-organization in avesta

In the article highlights the epistemological understanding of the features of self-formation in “Avesta”, its process, the principles reflect the determinants of knowledge of the world and ourselves in relationship, provide the scientific and conceptual analysis reflecting mechanisms of the spiritual and psychological self-formation of people.Scientific conclusions, proposals and recommendations on the constructive (creative) influence of the philosophical ideas of “Avesta” on the development of modern philosophical thought, its place in the spiritual and moral self-organization of people, in educating young people as patriots and humanists were developed. Developed proposals and recommendations for improving the mechanisms for the wide use of the possibilities of synergetic methodology in an even deeper awareness of the ontological, epistemological aspects of the scientific, philosophical ideas of “Avesta”.As a result of the objective study of “Avesta”, we substantiated that the early elements of the idea of self-organization began to carve their way with the appearance of this outstanding work, subsequently gave a powerful impetus to the formation of humanistic, dialectical, synergistic ways of thinking as a theoretical basis of scientific knowledge.It is the epistemological analysis of the idea of self-organization that not only increases the historical value of this category, characteristic of synergetic methodology, but at the same time determines the place of this category in the development of today's philosophical thought, and also directs the whole society to a decent self-organization, self-ordering only with such qualities as “creativity”, “Virtue”, etc. In order to consider the Avesta the earliest source in which issues of ontological, epistemological, epistemological, ecological, synergetic knowledge are highlighted, researchers need to further study this work more deeply, logically substantiate these findings and prove to the world scientific community. At the same time, it is the synergetic methodology that is of paramount importance. Of course, in development, in the progress of every state, of every society, in determining the prospects for their future, special attention is paid to the historical, spiritual heritage. Great history, high spiritual heritage serve as a reliable basis for a prosperous future. That is why the most effective results are provided by the analysis based on the synergistic methodology of such samples of rich spiritual heritage, like “Avesta”.

Formation of Hybrid Spatial Environment as a Multi- Agent System: Innovative Concepts

The article is devoted to the topical problem of forming a hybrid spatial environment as a multi-agent system. In the study have been identify the innovative concepts of the forming an architectural space as a multi-agent system that uses the technological innovations of the future. A forward-looking approach to the organization of spatial habitat as a multi-component system is propos. The leading approach to the study of this problem is based on analytical research methods: comprehensive design of the object as a system, the method of structural analysis, and the information technique. As a result, concepts of creating an artificial habitat using hybridization properties have been identify. Trends in modeling new types of spaces based on the idea of self-organization of the evolving system have been identifying.

Self-organized bistability and its possible relevance for brain dynamics

Self-organized bistability (SOB) is the counterpart of 'self-organized criticality' (SOC), for systems tuning themselves to the edge of bistability of a discontinuous phase transition, rather than to the critical point of a continuous one. The equations defining the mathematical theory of SOB turn out to bear strong resemblance to a (Landau-Ginzburg) theory recently proposed to analyze the dynamics of the cerebral cortex. This theory describes the neuronal activity of coupled mesoscopic patches of cortex, homeostatically regulated by short-term synaptic plasticity. The theory for cortex dynamics entails, however, some significant differences with respect to SOB, including the lack of a (bulk) conservation law, the absence of a perfect separation of timescales and, the fact that in the former, but not in the second, there is a parameter that controls the overall system state (in blatant contrast with the very idea of self-organization). Here, we scrutinize --by employing a combination of analytical and computational tools-- the analogies and differences between both theories and explore whether in some limit SOB can play an important role to explain the emergence of scale-invariant neuronal avalanches observed empirically in the cortex. We conclude that, actually, in the limit of infinitely slow synaptic-dynamics, the two theories become identical, but the timescales required for the self-organization mechanism to be effective do not seem to be biologically plausible. We discuss the key differences between self-organization mechanisms with/without conservation and with/without infinitely separated timescales. In particular, we introduce the concept of 'self-organized collective oscillations' and scrutinize the implications of our findings in neuroscience, shedding new light into the problems of scale invariance and oscillations in cortical dynamics.

ПЕДАГОГИЧЕСКАЯ СИНЕРГЕТИКА КАК СОСТАВЛЯЮЩАЯ ЛИЧНОСТНО ОРИЕНТИРОВАННОГО ОБУЧЕНИЯ В СОВРЕМЕННОЙ ШКОЛЕ

The prospects of the development of a modern school are mainly determined by the peculiarities of educational technologies available to teachers. Orientation towards the development of a child’s personality requires of schools the transition to the technologies based on the integration of traditional and innovative methods of teaching. The relevance of the study in the sphere of pedagogical synergy carried out by the author is determined by the unconditional need of society in the formation of an open education system and the willingness of teaching communities to work in the format relevant to the challenges of modern society. The paper considers the issue of formation of new approaches to the person-centered education, proves the reasonability of integration of traditional educational technologies and methods of social simulation through playing, focuses on the synergy of the interaction of diverse methods, which ensures high results of the educational process and opens for practicing teachers the unique possibilities of self-fulfillment and self-improvement. The author carried out the study in several directions: a systems analysis of the concepts of a personality-oriented approach to teaching and upbringing; defining the role and place of innovative educational technologies within the system of modern education; identifying the essence of a synergistic approach to pedagogical activity, and identifying the features of modeling and designing of pedagogical activity based on the idea of self-organization. The author carried out sociological research aimed at identifying the attitude of the participants of the educational process to the application of new teaching methods. The study revealed a positive attitude of the educational process participants to the idea of integration of teaching methods of different classes.

Decision-Making as a Self-Organizing Process

In this article, we present the analysis of the process of decision-making by applying the main concepts of complexity science linked with the theories of emotions. Decision-making in our personal or immediate social life concerns our future and involves surprises, uncertainty, and complexity. This is why complexity science, and especially the idea of self-organization is the most suitable for studying this unpredictable and surprising phenomenon. We propose that the process of decision-making in human life goes through three phases: The will phase, the choice phase, and the decision phase.

Methodology of Structural Stability Management for Industrial Enterprises

1. Introduction The disproportion in the development of enterprise structural elements due to different velocity of their growth and significant complexity of management objects because of their increasing diversity is nowadays one of the important problems of competition growth and industrial enterprises growth. The stated problem does not only decrease the company manageability as a system but increases costs connected with servicing and repair of technical objects as well. There are known researches in this field: BSC - Balanced Score Card, >--Smart-Safe-Sustainable systems (Trentesaux, 2009) and others to intellectualize of management process, to take into account all possible management system components which is provided by modern advances in the computer technology. Management intellectualization is performed on production and infrastructure levels, among which the exogenous subsystems are the most complex: assortment, production program, costs, labor rationing, innovative dynamics, ecological requirements and globalization of national economies indirectly decreasing enterprise stability have a special impact on the process of efficiency and stability support of the industrial enterprise in the period of continuous changes of the environment. Under such conditions it is important to consider the question of enterprise loss of some stability, which in terms of self-organized and interdisciplinary models reflects necessary economic, financial and technical stability, in the logic assessment system. Enumerated management models do not solve the tasks at full extend, as because they have limitations of cybernetic nature (a big number of changing objects), of statistic nature (it is not always possible to use average values for assessments) and of information nature (asymmetric information). Thus, the goal of the research is to justify of the possibility of using alternative tools to analyze the enterprise systems that remove the mentioned above limitations and allow assessing its structures in a whole on the basis of the criteria of local stability. 2. Theoretical and empirical research methods Our research is based on the ideas of self-organization, which attach great importance to structural formation of subsystems and elements of an industrial enterprise resulted from the competition between them for a resource. In terms of entropy approach and information theory there is nonlinear (exponential) dependence of an industrial enterprise on quality use of the limited resource which is difficult to watch due to the conditions of the industrial process and the development of a new methodological apparatus is required (Borangiu, 2012), and as we suppose it is to be performed in the frame of three spaces. In terms of technical systems we rely on concept of space >, meaning, for example, reliability, accessibility, safety, testability and maintainability of products, processes and industrial systems being assessed in terms of safety (Benard et al., 2008; Salimova and Makolov, 2016; Kormishkin et al., 2016). This aspect is to provide the necessary level of functionality and constant safety of all three types of state of any life cycle of systems. Reliability and stability are also interconnected with the notions of reaction and adaptation to perturbations in the process of their use, no matter of local or global nature (Bergstrom and other, 2015). This concept is not revolutionary as it is originally was used as a tool to analyze and design complex systems, when designers strived to develop efficient systems in terms of functionality including Integrated Logistic Support (ILS) and Providing functional support for production (PFSP) (Kriaa et al., 2015). It seems to be expedient to consider the question of safety providing in general by means of cybernetic model > (Sanislav et al., 2016). Space > is an intellectual measurement of product, processes and production systems and refers to the system which comprises computers, service-oriented solutions and means. …

White box, black box and self-organization

Purpose – The purpose of this paper is to present two system identification models – “white box” and “black box” – as useful tools that help understand self-organization processes within and outside the organizations facilitated by leaders. Every leader is presented as a “systems designer” who plays a fundamental role in the process of self-organization, both within and outside the organization under study. Design/methodology/approach – First, “white box” and “black box” system identification models are presented as a basis for an integrated model of the “system” and its “environment.” Next, the ideas of “closed” and “open” systems as the prerequisites of self-organization processes are described. Finally, two basic leadership tactics as well as their combination are characterized and discussed. Findings – Two system identification models give a complementary view to the reality, as they combine both reductionist and holistic perspectives. The argument presented in the paper shows that there is a far reaching complementarity of the two system identification models. Practical implications – Since leaders need to comprehend complex adaptive processes taking place in the organizations and in their environment, they search for the best strategy to approach this task. The tactics presented in the paper could serve as a cognitive tools that help approach the reality leaders are immersed in. Originality/value – The paper utilizes two categories that are well recognized in systems theory and cybernetics, combines them with the idea of self-organization and puts it all in the context of leadership. It provides an integrated, yet relatively simple cognitive scheme that may be of theoretical and practical use.

Nonlinear pedagogy: Learning design for self-organizing neurobiological systems

In this paper, key concepts in ecological psychology and nonlinear dynamics exemplify how learning design can be shaped by ideas of self-organization, meta-stability and self-organized criticality in complex neurobiological systems. Through interactions with specific ecological constraints in learning environments, cognition, decision making and action emerge. An important design strategy is the use of different types of noise to channel the learning process into meta-stable regions of the “learner–learning environment” system to encourage adaptive behaviors. Here learners can be exposed to many functional and creative performance solutions during training. Data from studies in the performance context of sports are used to illustrate how these theoretical ideas can underpin learning design. Based on these insights a nonlinear pedagogy is proposed in which the role of coaches or trainers alters from a more traditional, prescriptive stance to the mode of manipulating key interacting task constraints including information, space and equipment to facilitate learning.

Self-organisation in dynamical systems: a limiting result

There is presently considerable interest in the phenomenon of “self-organisation” in dynamical systems. The rough idea of self-organisation is that a structure appears “by itself” in a dynamical system, with reasonably high probability, in a reasonably short time, with no help from a special initial state, or interaction with an external system. What is often missed, however, is that the standard evolutionary account of the origin of multi-cellular life fits this definition, so that higher living organisms are also products of self-organisation. Very few kinds of object can self-organise, and the question of what such objects are like is a suitable mathematical problem. Extending the familiar notion of algorithmic complexity into the context of dynamical systems, we obtain a notion of “dynamical complexity”. A simple theorem then shows that only objects of very low dynamical complexity can self organise, so that living organisms must be of low dynamical complexity. On the other hand, symmetry considerations suggest that living organisms are highly complex, relative to the dynamical laws, due to their large size and high degree of irregularity. In particular, it is shown that since dynamical laws operate locally, and do not vary across space and time, they cannot produce any specific large and irregular structure with high probability in a short time. These arguments suggest that standard evolutionary theories of the origin of higher organisms are incomplete.

Autonomy-Oriented Search in Dynamic Community Networks: A Case Study in Decentralized Network Immunization

In recent years, immunization strategies have been developed for stopping epidemics in complex-network-like environments. Yet it still remains a challenge for existing strategies to deal with dynamically-evolving networks that contain community structures, though they are ubiquitous in the real world. In this paper, we examine the performances of an autonomy-oriented distributed search strategy for tackling such networks. The strategy is based on the ideas of self-organization and positive feedback from Autonomy-Oriented Computing (AOC). Our experimental results have shown that autonomous entities in this strategy can collectively find and immunize most highly-connected nodes in a dynamic, community-based network within a few steps.

Modeling Biological Manufacturing Systems with Bounded-Rational Agents

This paper presents bounded rationality as a characteristic of agents to develop their behavior in Biological Manufacturing Systems (BMS) that can deal with the complexity of the manufacturing environment using the ideas of self-organization, evolution and learning. Clarifying the definition and description of bounded rationality, the approach is implemented in an Ant System model. The purpose of the model is to handle the uncertainty in the perception, action and inner structure of agents by introducing bounded rationality in their characteristics. Computer simulation demonstrates the effectiveness of the approach by indicating significant improvement in the performance of the modeled BMS.

Kinetic Theory of Strength and a Self-Organized Critical State in the Process of Fracture of Materials

The basic principles of the Zhurkov kinetic approach are analyzed in light of the modern idea of self-organization of nonlinear systems under nonequilibrium conditions. It is indicated that the final state before fracture can be described in terms of the model of a self-organized critical state.

The effect of special features of forming the imperfect structures in germanium crystals on plastic properties of these crystals

A new technology for forming the structures in semiconductor crystals using plastic deformation in an electric field is suggested. A setup making it possible to implement the suggested method and study the idea of self-organization of dislocation-related dissipative structures is described.

Facility Layout Planning Using Self-Organization Method

This paper proposes a novel approach to facility layout planning based on the concept of biological manufacturing systems that deal with the inherent complexity of manufacturing using ideas of self-organization, evolution and learning. A self-organization method is proposed to generate facility layout plans autonomously according to the material flow which emerges from the local interactions among production elements. A case study of facility layout planning is presented for semiconductor manufacturing, in which it is difficult to find a proper layout because of complex process flow. The effectiveness of the proposed method is discussed in terms of the accumulated traveling distance of products and the throughput.

Line-less Production System Using Self-Organization: A Case Study for BMS

The paper proposes a novel approach to the design of line-less production systems. The approach is based on the concept of biological manufacturing systems (BMS) that can deal with complexity in manufacturing using the ideas of self-organization, evolution and learning. In the line-less production systems, all production elements can move freely on the production floor using self-organization in order to adapt to fluctuations such as the diversity of production demands and the malfunction of machines. The effectiveness of the line-less production system is discussed and its feasibility is demonstrated by computer simulation. Furthermore, a mini-factory consisting of small autonomous robots is developed as a prototype of the line-less production systems.

Rainfall Disaggregation Using Artificial Neural Networks

A precipitation time series is often a necessary input for the analysis and design of hydrologic and hydraulic systems. The precipitation records employed for these purposes can be either measured observations or generated by stochastic simulation. One common problem with recorded and generated precipitation data is that often it is not in small enough time increments for use in engineering applications (e.g., continuous hydrologic simulation). To solve this problem, rainfall amounts can be disaggregated into shorter time increments. This paper evaluates the use of artificial neural networks (ANNs) for the disaggregation of hourly rainfall data into subhourly time increments. Two different ANN models are introduced and evaluated in this paper. A back-propagation/steepest-descent algorithm trains one model and the other model uses the idea of self-organization in a competitive learning ANN. The results indicate that the performance of both ANN models are: (1) comparable to other disaggregation schemes in terms of predicting the overall disaggregated rainfall hyetograph; and (2) improvements over other disaggregation models in the prediction of the maximum incremental rainfall intensity (depth) within a storm hyetograph. Based on these results, the use of ANN models can be recommended as a viable alternative for hourly rainfall disaggregation.