Cyber-social Systems Research Articles

Social System Inference From Noisy Observations

This article studies social system inference from a single noisy trajectory of public evolving opinions, wherein observation noise leads to the statistical dependence of samples on time and coordinates. We first propose a cyber-social system that comprises individuals in a social network and a set of information sources in a cyber layer, whose opinion dynamics explicitly takes the asymmetric cognitive bias including confirmation bias and negativity bias and the process noise into account. Based on the proposed cyber-social model, we then study the sample complexity of least-square auto-regressive model estimation, which governs the length of a single observed trajectory that is sufficient for the identified model to achieve the prescribed levels of accuracy and confidence (PAC). Building on the identified social model, we then investigate social inference, with a particular focus on the weighted network topology and the model parameters of asymmetric cognitive bias. Finally, the theoretical results and the effectiveness of the proposed inference framework are validated by the U.S. Senate Member Ideology data.

APPLICATION OF GAME MODELS IN THE MANAGEMENT OF CYBER-PHYSICAL SYSTEMS

Cyber-physical systems (CPS), along with cyber-biological and cybersocial systems, have recently become one of the key elements of modern infotelecommunications systems. The Internet of Things, as a revolutionary concept of the past few years, is a fundamental concept in the context of SPS. However, unlike the Internet of Things, which primarily emphasizes machine-to-machine connections, the SPS concept is based on the dualism of physical and cybernetic (information) environments. Turning to the applied field, we should note the trend towards informatization of many elements of the world around us. The degree of penetration ranges from sensors transmitting information about the state of a living organism to precise models describing the current state of an element within a smart production. This paper deals with the problem related to the control of cyber-physical systems under conditions where various random external influences are exerted on them. On the basis of game theory, the paper proposes, taking into account various criteria, to carry out the choice of control. Examples of calculations are considered.

A Framework for Digital Development of Industrial Systems in the Strategic Drift to Industry 5.0

Industry 5.0 is an integral driving force for industrial development to overcome a resurgent strategic drift. This solution is a perfect tool to ensure a sustainable, human-centered, and resilient industry and encourage man-machine collaboration within intelligent cyber-social systems. A complete shift to Industry 5.0 is only feasible when industrial systems apply digital strategizing to enhance digital development. That would invite technologies and humans to facilitate all operational and customer dealings, significantly increasing the rate of innovation. This research aims to articulate a multi-perspective conceptual framework based on the premises of digital development of industrial systems in the strategic drift to Industry 5.0. The methodology implied in this research rests on an interview with industry experts, a case study of digitalization leaders in 2021, extensive and systematic literature review and scientometric analytical tools, content analysis and foresight. In this paper, the authors reframe the concept of digital strategy and consider it as a notion independent of digitalization strategy and digital transformation strategy that is traditionally based on the formation of digital thinking, implementation of digital behavior patterns, the transformation of mindset, and strategic wisdom. As a result, a brand-new perspective on Industry 5.0 is suggested

Artificial intelligence in the long view: from mechanical intelligence to cyber-social systems

Artificial intelligence (AI) is emerging as a defining technology of our time, a source of fear as often as inspiration. Immersed in its practicalities, rarely do we get to ask the question, what is it? How does it impact our lives? How does it extend our human capacities? What are its risks? What are its limits? This paper is a theoretical and historical overview of the nature of binary computing that underpins AI and its relations with human intelligence. It also considers some philosophical questions about the semiotic or sense-creating work of computers. Our argument proceeds in five steps. We begin with an historical background: since Ada Lovelace, we have wondered about the intelligence of machines capable of computation, and the ways in which machine intelligence can extend human intelligence. Second, we ask, in what ways does binary computing extend human intelligence and delimit the scope of AI? Third, we propose a grammar with which to parse the practical meanings that are enabled with and through binary computing. Through this discussion, we raise the question of ontology as a counter-balance to what we will argue has been an over-emphasis on the instrumental reasoning processes of the algorithm. Fourth, we situate binary computing in the context of broad developments in modern societies which we characterize as a series of systems transitions: from industrial, to informational, to a new phase that we term “cyber-social.” Finally, we explore the risks inherent in a pervasively cyber-social system. These are narrowly captured in the technical domain, “cybersecurity.” We set out to reconceive this problem framework as the location for a potential solution, supplementing analyses of cybersecurity risk with a program of cyber-social trust.

Моделирование нарративного управления в социально-экономических системах

The article considers approaches to modeling management process in socio-economic systems. A management model is proposed, in which goal-setting is considered as a dynamic process that forms the controlled development of a socio-economic system at all stages of its life cycle. Goal achievement is understood as the activity of management process participants for achieving a given general goal in a dynamically formed goal space. Management is modeled as a trade-off between goal setting and goal achievement, the ultimate goal of which is ensuring the existence of the system and the fulfillment of its mission, assigned by the system environment. The fulfillment of the system mission in the context of its continuous interaction with the environment requires continuous collecting and processing data on the current state of the system and its environment, constant monitoring, analysing information flows as information carriers necessary for making prompt and informed management decisions. Socio-economic systems having computing resources that ensure the management of information flows are considered as cyber-social systems. The management process in socio-economic systems is considered in terms of narrative practice, therefore, within the framework of the narrative management model, human behavior as a subject and object of management in a socio-economic system is not modeled fundamentally. Mathematical models allowing formalization and reasonable interpretation in terms of a real simulated system are proposed to support the management stages. The architecture of the software package for supporting narrative management is given, in which the proposed models are implemented

Super-metauniverse with cyber life as center in integrating cyber nature and cyber society sky-earth computing (III) beyond cloud computing

According to the analysis and design of this series of articles, with cyber life as the center, using big data platform, IOT, AI technology, and the super-metauniverse system engineering that we advocate to develop and implement, we integrate cyber natural system and cyber social system, and establish a super-metauniverse system (SMS) for the hyper cyber-world. cyber life system is a life system supported by IT and network technology, including cyber physiological system (CPS-2) and cyber psychological system (CPS-3); Cyber natural system is a natural system supported by IT and network technology, including cyber physical system (CPS-1); Cyber social system is a social system supported by IT and network technology, including cyber eventlogic system (CES). Therefore, it is necessary between the real ecosphere and the information ecosphere to organize and manage not only thousands of computers, mobile communication tools and robots thousands of computers, mobile communication tools and robots, but also thousands of people who use computers, mobile communication tools and robots, through the Internet of things, artificial intelligence technology, the bottom layer of big data computing platform, and the super-metauniverse system engineering proposed in this series of articles.

Cyber-Physical-Social Systems: Taxonomy, Challenges, and Opportunities

A Cyber-Physical-Social System (CPSS) is a novel paradigm of cyber-physical and cyber-social systems with a highly inhomogeneous and distributed nature integrating dynamic stochastic hybrid systems including computation, communication, sensing and actuation, and social systems.Their usage can be traced to homes such as smart homes, manufacturers in Industry 5.0, critical infrastructures, smart cities, medicines, healthcare systems, and many other examples. They can simplify and speed up tasks and provide a higher level of control and accessibility. In this study, we provide a systematic review of the definition of CPSS,and an uniform definition of CPSS. We propose a novel taxonomy to define CPSS to help future researches and system designing. The CPSS taxonomy aims to provide a comprehensive and understating of CPSS characteristics and aspects from system-to-system point of view. Furthermore, we discuss about social integration in CPSS and their relationships with CPS. We mention issues and opportunities in CPSS in the designing and implementing phases.

Industry 5.0: concept, formation and development

At present in Europe and Russia there are active discussions of the next mega stage of human social and economic development. It concerns the Industry 5.0 concept. In 2020–2021 members of scientific research and technological organizations discussed the aspects of Industry 5.0 at a number of well-known European and Russian forums. Major attention was paid to technologies maintaining Industry 5.0. As a result the world scientific community reached a consensus on two fronts: firstly, on integration of opportunities of the existing technologies of Industry 4.0 with the human-oriented approach of Industry 5.0 which will give way to harmonious interaction of human intelligence with cognitive calculations; and, secondly, on integration of human and machine intelligence to create collective intelligence which will make it possible to avoid technological singularity in future as well as provide for simultaneous humans’ evolution and technologies’ development. These will become the basis for creating a fundamentally new social, economic and cultural strategy of the society’s development for the coming decades. The strategy is based on applying collective intelligence and meta-system technologies in all spheres of life. For the first time in the world scientific practice the authors introduce the concept of Industry 5.0 as a cyber social system which allows the alliance of human and artificial intelligence aimed at creating collective super intelligence and becomes a source of harmonious technological development of human civilization. The authors present a neuro-ecosystem model of Industry 5.0 concept which will make it possible to set the task of implementing the systems of global meta-system strategized development of cognitive production and industry. Such systems are established as part of organization of cognitive production and new types of social and economic, cyber-social and industrial ecosystems by means of implementing collective intelligence and neuro-digital meta-technologies. This is the first stage of a new evolution process of developing Industry 4.0 concept, transition to Industry 5.0 and to meta-system transformations economics.

Cyber-animism: the art of being alive in hybrid society

The boundaries of social acceptance and models of convergence of human and non-human (for example, subjects of artificial intelligence) actors of digital reality are defined.The constructive creative possibilities of convergent processes in distributed neural networks are analyzed from the point of view of possible scenarios for building “friendly” human-dimensional symbioses of natural and artificial intelligence. A comprehensive analysis of new management challenges related to the development of cyber-physical and cybersocial systems is carried out.A model of social organizations and organizational behavior in the conditions of cyberphysical reality is developed.The possibilities of reconciling human moral principles and “machine ethics” in the processes of modeling and managing digital reality are studied. The significance of various concepts of digital, machine and cyber-anymism for the socio-cultural understanding of the development of modern cyber-physical technologies, the anthropological dimension of a smart city is revealed. The article introduces the concept of hybrid society and shows the development of its models as self-organizing collective systems that consist of co-evolving biohybrid and socio-technical spheres. The importance of modern anthropogenic research for sustainable development is analyzed. The process of marking ontological boundaries between heterogeneous modalities in the digital world is investigated. Examples of acute social contexts that are able to set the vector of practical philosophy in the modern digital era are considered.

Analysis and Controlling of Manufacturing Service Ecosystem: A Research Framework Based on the Parallel System Theory

With the development of cloud manufacturing technology, Manufacturing Service Ecosystem (MSE) is emerging as a typical complex cyber-social system. On the one hand, service strategy (cyber layer) drives the evolution of manufacturing community (social layer); on the other hand, the initial conditions of manufacturing community (social layer) affect the performance of service strategy. In order to promote the evolution of MSE in the expected direction, it is necessary to clarify the loop feedback mechanism between heterogeneous networks. However, how to analyze and intervene in the possible evolution directions of MSE has become a serious challenge in the field. In order to face this challenge, this paper proposes a parallel system theory-based research framework to study the evolution and controlling of MSE. First, the corresponding digital system of MSE is constructed from the perspective of supply and demand matching. Second, the specific computational experiment is executed to present the effect of different service strategies (cyber layer) and different initial conditions (social layer) on the evolution of MSE. Furthermore, the comparison of experiment results with real data verifies the credibility of the proposed approach. It demonstrates that our approach can provide a new way for analyzing the complexity of MSE.

Differentially private data fusion and deep learning Framework for Cyber–Physical–Social Systems: State-of-the-art and perspectives

The modern technological advancement influences the growth of the cyber–physical system and cyber–social system to a more advanced computing system cyber–physical–social system (CPSS). Therefore, CPSS leads the data science revolution by promoting tri-space information resource from a single space. The establishment of CPSSs increases the related privacy concerns. To provide privacy on CPSSs data, various privacy-preserving schemes have been introduced in the recent past. However, technological advancement in CPSSs requires the modifications of previous techniques to suit its dynamics. Meanwhile, differential privacy has emerged as an effective method to safeguard CPSSs data privacy. To completely comprehend the state-of-the-art developments and learn the field’s research directions, this article provides a comprehensive review of differentially private data fusion and deep learning in CPSSs. Additionally, we present a novel differentially private data fusion and deep learning Framework for Cyber–Physical–Social Systems , and various future research directions for CPSSs.

Multiplayer Noncooperative and Cooperative Minimax H∞ Tracking Game Strategies for Linear Mean-Field Stochastic Systems With Applications to Cyber-Social Systems.

The multiplayer stochastic noncooperative tracking game (NTG) with conflicting target strategy and cooperative tracking game (CTG) with a common target strategy of the mean-field stochastic jump-diffusion (MFSJD) system with external disturbance is investigated in this study. Due to the mean (collective) behavior in the system dynamic and cost function, the designs of the NTG strategy and CTG strategy for target tracking of the MFSJD system are more difficult than the conventional stochastic system. By the proposed indirect method, the NTG and CTG strategy design problems are transformed into linear matrix inequalities (LMIs)-constrained multiobjective optimization problem (MOP) and LMIs-constrained single-objective optimization problem (SOP), respectively. The LMIs-constrained MOP could be solved effectively for all Nash equilibrium solutions of NTG at the Pareto front by the proposed LMIs-constrained multiobjective evolutionary algorithm (MOEA). Two simulation examples, including the share market allocation and network security strategies in cyber-social systems, are given to illustrate the design procedure and validate the effectiveness of the proposed LMI-constrained MOEA for all Nash equilibrium solutions of NTG strategies of the MFSJD system.

An improved localization method in cyber-social environments with obstacles

In Cyber-Social Systems (CSS), sensors play a key role in the intelligent perception and recognition of people, objects and the environments, in which target localizing is one of the important issues. It is often difficult to accurately and conveniently localize the sensors due to the presence of Non-Line Of Sight (NLOS) when there are obstacles. This paper proposes a sensor localization method based on WiFi (Wireless Fidelity) localization, which first collects the angle and intensity information of the WiFi signals of mobile base stations during a linear or curvilinear motion, then uses the Nonlinear Inequality Constrained-Unscented Kalman Filter (NIC-UKF) method presented in this paper to filter interference, so as to localize the positions of sensors. The method has stronger stability, high precision, and acceptable computing overhead, which is suitable for the localization of fixed or low-speed moving targets in Cyber-Social environments with obstacles.

Resource Provisioning for Cyber–Physical–Social System in Cloud-Fog-Edge Computing Using Optimal Flower Pollination Algorithm

The rise of cyber-physical-social systems (CPSS) as a novel paradigm has revolutionized the relationship among humans, computers and physical environment. The key technologies to design CPSS directly related to multi-disciplinary technologies including cyber-physical systems (CPS) and cyber-social systems (CSS). Unfortunately, the design of CPSS is not an easier process because of the network heterogeneity, complex hardware and software entities. At the same time, fog computing is emerged as an expansion of cloud computing which efficiently addresses the abovementioned issue. Resource provisioning is a main technology involved in fog computing. This paper devises a novel fuzzy clustering with flower pollination algorithm called FCM-FPA as a resource provisioning model for fog computing. At the earlier stage, the resource attributes are standardized and normalized. Next, the fuzzy clustering with FPA is developed for partitioning the resources and the scalability of resource searching has been minimized. At last, the presented resource provisioning algorithm based on optimized fuzzy clustering has been devised. The performance of the proposed FCM-FPA model has been tested using a set of two benchmark Iris and Wine dataset. The experimental outcome ensured that the FCM-FPA model has shown proficient results over the compared methods by offering maximum user satisfaction and effective resource provisioning.

Cyber-Social Systems: Modeling, Inference, and Optimal Design

This paper models the cyber-social system as a cyber-network of agents monitoring states of individuals in a social network. The state of each individual is represented by a social node and the interactions among individuals are represented by a social link. In the cyber-network each node represents an agent and the links represent information sharing among agents. Agents make an observation of social states and perform distributed inference. In this direction, the contribution of this work is threefold: (i) A novel distributed inference protocol is proposed that makes no assumption on the rank of the underlying social system. This is significant as most protocols in the literature only work on full-rank systems. (ii) A novel agent classification is developed, where it is shown that connectivity requirement on the cyber-network differs for each type. This is particularly important in finding the minimal number of observations and minimal connectivity of the cyber-network as the next contribution. (iii) The cost-optimal design of cyber-network constraint with distributed observability is addressed. This problem is subdivided into sensing cost optimization and networking cost optimization where both are claimed to be NP-hard. We solve both problems for certain types of social networks and find polynomial-order solutions.

Modelling Subject Domain Causality for Learning Content Renewal

The paper deals with the causality driven modelling method applied for the domain deep knowledge elicitation. This method is suitable for discovering causal relationships in domains that are characterized by internal circular causality, e.g. control and management, regulatory processes, self-regulation and renewal. Such domains are organizational systems (i.e. enterprise) or cyber-social systems, also biological systems, ecological systems, and other complex systems. Subject domain may be of different nature: real-world activities or documented content. A causality driven approach is applied here for the learning content analysis and normalization of the knowledge structures. This method was used in the field of education, and a case study of learning content renewal is provided. The domain here is a real world area – a learning content is about. The paper is on how to align the existing learning content and current (new) knowledge of the domain using the same causality driven viewpoint and the described models (frameworks). Two levels of the domain causal modelling are obtained. The first level is the discovery of the causality of the domain using the Management Transaction (MT) framework. Secondly, a deep knowledge structure of MT is revealed through a more detailed framework called the Elementary Management Cycle (EMC). The algorithms for updating the LO content in two steps are presented. Traceability matrix indicates the mismatch of the LO content (old knowledge) and new domain knowledge. Classification of the content discrepancies and an example of the study program content analysis is presented. The main outcome of the causality driven modelling approach is the effectiveness of discovering the deep knowledge when the relevant domain causality frameworks are applicable.

What's the Folk Theory? Reasoning About Cyber-Social Systems

The present paper explores people’s folk theories of cyber-social systems by identifying the metaphors people hold and then analyzing them semantically for underlying attitudes and beliefs. In Study 1 (N = 3375) we use a novel method for eliciting metaphors for how people understand the Facebook News Feed and Twitter. In Study 2 (N = 1547) we used factor analysis to aggregate these metaphors into underlying folk theories for both Facebook and Twitter. In Study 3 (N = 1597) we replicate the factor analysis from Study 2 and examine the semantic dimensions for each of the folk theories across these two cyber-social systems, finding that there are four primary folk theories that people hold for the News Feed and Twitter: the rational assistant, the unwanted observer, the transparent platform and the corporate black box. The implications of identifying and understanding these folk theories for these cyber-social systems are discussed.

The science of Learning Health Systems: Foundations for a new journal.

The science of Learning Health Systems: Foundations for a new journal.

A survey: Cyber-physical-social systems and their system-level design methodology

The emergence of cyber-physical-social systems (CPSS) as a novel paradigm has revolutionized the relationship between humans, computers and the physical environment. In this paper, we survey the advancement of CPSS through cyber-physical systems (CPS), cyber-social ​systems (CSS) and CPSS, as well as related techniques. CPSS are still at their infancy, most recent studies are application-specific and lack of systematic design methodology. To exploit the design methodology for CPSS, we review the existing system-level design methodologies in multiple application domains and further compare their performance characteristics and applicability for CPSS. Finally, we introduce our latest research advancement on system-level design methodology for CPSS and summarize future challenges for designing CPSS.

Physical-Cyber-Social Computing: Looking Back, Looking Forward

Physical-cyber-social (PCS) computing involves a holistic treatment of data, information, and knowledge from the physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans and the applications that serve them. PCS computing extends current progress in cyber-physical, socio-technical, and cyber-social systems. Here, the guest editors consider powerful ways to exploit data available through various Internet of Things (IoT), citizen and social sensing, Web, and open data sources that are seeing explosive growth. This special issue highlights a variety of PCS applications, such as smart firefighting, intelligent infrastructure, and user guidance in an airport.