Introducing Change into Complex Cognitive Work Systems

The complexity of problems facing society continues to grow, and decision-makers and problem-solvers are finding many of today's emerging problems to be beyond their capability to adequately address. There is agreement in the literature that problems of this nature are complex system problems, inextricably linked to some highly complex system of systems. Establishing a clear understanding of the specific complex system context is fundamental to the process of understanding and analyzing complex systems and complex system problems across all of the different systems-based disciplines. While complex system context is widely referred to in systems literature, there is no clear characterization of exactly what system context is, making this foundational system concept ambiguous. This research addressed this gap in the systems body of knowledge by providing the needed detail and clarity to the concept of complex system context. A rigorous research methodology, employing the grounded theory method, was used to analyze data collected through a series of semi-structured interviews conducted with individuals reflecting a wide range of systems education and practical experience. Two research questions were identified as integral to increasing the understanding of context within complex systems. (1) What are the constituent elements of complex system context, and what attributes and dimensions characterize these elements? (2) What systems-based framework can be developed for constructing and articulating complex system context? Using the grounded theory method, a theory of system context was constructed, adding to the systems body of knowledge and substantiating a comprehensive and unambiguous theoretical construct for system context within complex systems. Then, based on this theory, a conceptual model to articulate and capture system-specific complex system context was developed---the Complex System Contextual Framework (CSCF). The CSCF shows significant promise for contribution to systems practitioners by supporting the future development of tools to help practitioners capture system context as a part of complex system problem formulation. The research also made a contribution in the area of research methodologies by furthering the use of the grounded theory method in the engineering management and systems engineering domain, an area where its application has been very limited.

Linguistic Geometry for autonomous navigation

Regional complex system simulation optimization through linking governance and environment performance: A case study of water environmental carrying capacity based on the SDES model

Contracts as Systems

The 17 Sustainable Development Goals (SDGs) are a complex system comprising 169 targets and about 230 indicators. Urban Health could be considered a complex system since it deals with 15 out of 17 SDGs, excluding the two related to life below water and life on land. According to the World Health Organization, to achieve the SDGs, countries have committed to organize Urban Health initiatives to improve the social, economic, and physical environments promoting health and sustainability globally. Cities will become more inclusive, safer and more sustainable, which are important driving forces to implement the development equation. To set up a framework to point out that Urban Health is a complex system oriented to the achievement of the SDGs. It has been conducted an extensive literature review on databases (PubMed, Embase, Web of Science and Scopus) using keywords in 3 strings combined with Boolean operators: SDGs and Urban Health, Urban Health as Complex System and Urban Health, Environmental Health and Public Health as Complex Systems. In addition, a grey literature review has been carried out. Out of 1005 publications, 21 were eventually included: 14 publications relate to the interdependent relationships between SDGs and Urban Health, with regard to the association between Urban Health and complex system, 3 publication studied the effects and implications of such correlation, 4 focused on Environmental Health and Public Health in relation with the complex system. The selected publications suggested methodologies aimed at setting up an urban health framework to achieve SDGs. There is an initial orientation focused on the study of Urban Health problems aimed at achieving SDGs from the perspective of complex systems. We highlight the need to conduct further studies on a more detailed framework in order to address this type of approach.

The evaluation of the emergent behaviour in complex systems requires an analytical framework which allows the observation of different phenomena that take place at different levels. In order to observe the dynamics of complex systems, it is necessary to perform simulations so that both local and the emergent behaviour can be observed. To this end, the way in which complex system simulators are built must be examined so that it will be feasible to model large scale scenarios. In this paper, the use of Model Driven Engineering methodology is proposed to deal with this issue. Among other benefits, it is shown that this methodology allows the representation and simulation of a complex system providing support for the analysis. This analysis is supported by a metamodel which describes the system components that are under study. The application of this methodology to the development of large scale simulators is explored through a case study. This case study analyses a complex socio-technical system: a power grid.

Public health evaluation methods have been criticized for being overly reductionist and failing to generate suitable evidence for public health decision-making. A "complex systems approach" has been advocated to account for real world complexity. Qualitative methods may be well suited to understanding change in complex social environments, but guidance on applying a complex systems approach to inform qualitative research remains limited and underdeveloped. This systematic review aims to analyze published examples of process evaluations that utilize qualitative methods that involve a complex systems perspective and proposes a framework for qualitative complex system process evaluations. We conducted a systematic search to identify complex system process evaluations that involve qualitative methods by searching electronic databases from January 1, 2014-September 30, 2019 (Scopus, MEDLINE, Web of Science), citation searching, and expert consultations. Process evaluations were included if they self-identified as taking a systems- or complexity-oriented approach, integrated qualitative methods, reported empirical findings, and evaluated public health interventions. Two reviewers independently assessed each study to identify concepts associated with the systems thinking and complexity science traditions. Twenty-one unique studies were identified evaluating a wide range of public health interventions in, for example, urban planning, sexual health, violence prevention, substance use, and community transformation. Evaluations were conducted in settings such as schools, workplaces, and neighborhoods in 13 different countries (9 high-income and 4 middle-income). All reported some utilization of complex systems concepts in the analysis of qualitative data. In 14 evaluations, the consideration of complex systems influenced intervention design, evaluation planning, or fieldwork. The identified studies used systems concepts to depict and describe a system at one point in time. Only 4 evaluations explicitly utilized a range of complexity concepts to assess changes within the system resulting from, or co-occurring with, intervention implementation over time. Limitations to our approach are including only English-language papers, reliance on study authors reporting their utilization of complex systems concepts, and subjective judgment from the reviewers relating to which concepts featured in each study. This study found no consensus on what bringing a complex systems perspective to public health process evaluations with qualitative methods looks like in practice and that many studies of this nature describe static systems at a single time point. We suggest future studies use a 2-phase framework for qualitative process evaluations that seek to assess changes over time from a complex systems perspective. The first phase involves producing a description of the system and identifying hypotheses about how the system may change in response to the intervention. The second phase involves following the pathway of emergent findings in an adaptive evaluation approach.

As chief-editor of an academic journal, one has the prerogative to read a lot of “raw material”; (concepts of-) papers that may (or may not) make it as a publication to the journal. Jointly, these “raw” papers certainly give a most interesting insight in ongoing research activities in the academic and industrial world. We as authors, recognize availability of “highly important sub-system A” as of crucial importance for the operation of “complex system B”. Therefore we have done a case-study on how to improve the availability of “sub-system A” using the following method “variant of a availability/maintenance analysis/optimization method already existing since the mid-20th century”. It has led to the following improvement… Especially when “sub-system A” is of a very traditional, often mechanical, nature we have to decline this paper due the fact that only very limited conceptual new knowledge is generated in spite of the, without any doubt, valuable contribution to the owners of “complex system B.” We as authors have studied the following methodological concepts “A, B, C, D, …” and have come to the conclusion that it is worthwhile to develop a new concept “E” which looks as follows “complex mathematical description”. Compared to the earlier described methods this leads to the following, conceptual, advantages “list of tables/graphs”. Application: highly conceptual or absent. Also, in this case, papers are often declined since the innovative contribution to the resolution of real-world (engineering) problems is often very limited. And, in the real-world, major engineering challenges remain unsolved. I am writing this paper for a very specific reason: in our daily life, society has become increasingly dependent on the availability of complex systems. With the recent hurricanes Harvey, Irma, and Maria, we have seen that the destruction caused not only the traditional primary systems to fail (water, food, etc.) but also the more recent primary systems (transportation, energy, communication/internet, etc.) The unavailability of, especially, these more recent primary systems is also often causing delay in the restauration of the more traditional primary systems. In all cases, the impact for the people involved is considerable. What amazes me in this context is that, although major events like hurricanes have happened in the past and will happen (according to some models even increasingly) also in the future, no case studies have been proposed to journals like this on how to analyze the availability of these highly important (but also highly complex and interwoven) systems under these extreme conditions. Even more valuable would be proposals not only on how to analyze these systems but also on how engineers could make them more robust. In the 21st century, we have become highly dependent on the availability of highly sophisticated systems like the Internet because of the most valuable services they provide but studies on how to analyze and improve their availability in a 21st-century context are still missing!

This paper presents the setup, the assessment methods, and the results of a flight trial that was conducted in June 2016 in order to demonstrate integration of remotely piloted aircraft systems (RPAS) into the current airspace, while also acknowledging that there are challenges to overcome. An RPAS demonstrator received a flight plan from the ground control station (GCS) using a ground-based data link, departing from Braunschweig-Wolfsburg airport and flying towards Leipzig/Halle airport on published routing. When approaching Leipzig/Halle airport, the data link was lost as predicted, and the arrival procedure was altered by air traffic control (ATC), which showed that an additional and dedicated RPAS controller at arrival airports might be valuable and advantageous. Focus of this paper is the description of the components that were used during the trial and their interconnectivity, the evaluation of quantitative recorded data and the qualitative experienced difficulties and challenges. Assessment of the recorded data is divided into data link quality, data link latency, and flight following performance (vertical and lateral following accuracy), with the latter being linked to existing performance based navigation (PBN) parameters by ICAO and height-keeping performance values by EASA. The paper concludes with a discussion on the investigated integration concept.

The coordinated development of a complex system refers to the harmonious and coherent evolution of its subsystems. From the perspective of the coordinated development of ecological–economic–social complex systems, this paper analyzes the coordinated development mechanism (CDM) of the mariculture ecological–economic–social (MEES) complex system, constructs a coordinated development evaluation indicator system for the MEES complex system, and adopts the comprehensive evaluation model and the coupling coordination degree (CCD) model to empirically analyze the coordinated development level of the MEES complex system in China from 2009 to 2020. The results show that the comprehensive development level of China’s MEES complex system has improved significantly during this period, with the comprehensive development index increasing from 0.25 in 2009 to 0.76 in 2020, transitioning from a poor to an excellent status. Simultaneously, the CCD of the system increased progressively, experiencing phases of near dissonance, barely coupling coordination, primary coordination, and intermediate coordination, before finally reaching a stage of good coordination. Based on these findings, we further discuss and propose countermeasures to promote the coordinated development of China’s MEES complex system.

This introductory chapter provides an overview and a brief history of complexity science, which is the study of complex systems. All living systems and all intelligent systems are complex systems. Complexity science is relatively new but already indispensable. Many of the most important problems in engineering, medicine, and public policy are now addressed with the ideas and methods of complexity science. However, there is no agreement about the definition of 'complexity' or 'complex system', nor even about whether a definition is possible or needed. The conceptual foundations of complexity science are disputed, and there are many and diverging views among scientists about what complexity and complex systems are. Even the status of complexity as a discipline can be questioned given that it potentially covers almost everything. The origins of complexity science lie in cybernetics and systems theory, both of which began in the 1950s. Complexity science is related to dynamical systems theory, which matured in the 1970s, and to the study of cellular automata, which were invented at the end of the 1940s. By then computer science had become established as a new scientific discipline.

An Agent-Based Approach to Aircraft Conflict Resolution with Constraints

In many ways, Physics Today is a complex system. Like other such systems, it is subject to diverse stimuli and constraints, any of which could arise from within or be imposed from without. Like other complex systems, this magazine evolves continually in response to those various stimuli and constraints, and the rules that govern our evolution are often difficult to discern. Sometimes we evince dramatic changes; usually we do not. You will notice some changes this month.Perhaps most immediately obvious are the cosmetic changes that we’ve made throughout our regular departments. The result is a bolder look that we think gives you better visual landmarks. We hope you like it as much as we do.Far more important, this month we introduce a new department, “Issues and Events.” It is a natural, evolutionary change that combines two previous departments, “Washington Reports” and “Physics Community.” The melding of those departments recognizes that the geopolitical, social, and financial aspects of our science are all of great importance and are inextricably interwoven. “Issues and Events” appears immediately following “Search and Discovery” as an acknowledgment of the close coupling between the science we enjoy doing and the world in which we do it. As always, our coverage in “Issues and Events” reflects our belief that Physics Today, as a monthly publication, best serves you by providing context for the news, not by trying to cover every breaking story. Within our pages, we strive to discuss things that really matter to you; and perhaps have a little fun along the way.The ever-popular “We Hear That” department, covering people-related news such as society elections, awards, and job changes, can still be found near the back of the magazine. There since 1950, it provides striking testimony that some elements of complex systems are remarkably robust.Drivers of change in complex systems take many forms. The explosive growth of the Internet is a driver familiar to us all. If you have not recently visited http://www.physicstoday.org, take a look. You will be surprised. Beginning with the July 2000 issue, the complete contents of Physics Today are now available online. All the articles. Every book review and letter. All the news stories. Even new product announcements. Everything you find between our covers, you will find online. An eduring joy of our work at Physics Today is the wonderful spirit of cooperation we experience with you.On our Web site, we also routinely provide links to related material, both from our pages and beyond. For example, with our special issue on national security last month, we posted more than 160 pages of archival material from earlier issues of Physics Today. When the right opportunities arise, we will also experiment with discussion forums as an additional service.Our mission remains to keep you informed about science and its place in the world. Even as you depend on us for information, our success in providing it depends on you. Over the course of a year, we send thousands of e-mails and make thousands of calls to you, our readers. Whether we need to clarify a scientific matter, find a route through a tangled political thicket, learn about your field’s (or someone else’s) latest developments, or seek suggestions and advice on matters great and small, an enduring joy of our work is the wonderful spirit of cooperation we experience with you. For that, we are very grateful.This year, we will call on some of you in a different way. One of our greatest challenges at Physics Today is to understand what we don’t already know, to push back the limits of our ignorance as you push forward the frontiers of our science. Ironically, one of the things we know the least about is you, and how well we are serving you. Beginning next month, we will be e-mailing an editorial survey questionnaire to random samples of you. We have put the same care into formulating our questions to you that we put into every issue of this magazine. We are eager to receive your answers. With that important stimulus, this complex system will continue to evolve in a manner appropriate to us all.Stephen G. BenkaPPT|High resolution© 2001 American Institute of Physics.

The theoretical biologist, Robert Rosen, proposed that a capacity for anticipatory change is a fundamental characteristic of most complex systems, including all living systems. As defined in his Anticipatory Systems: Philosophic, Mathematic, and Methodological Foundations, an anticipatory system contains “a predictive model of itself and/or its environment, which allows it to change state at an instant in accord with the model’s prediction pertaining to a later instant”. In Rosen’s view, two key features which differentiate anticipatory complex systems from “simple” mechanistic systems are: (1) no single formal model or finite set of models are capable of capturing all of the information in a complex system, and (2) anticipatory complex systems are capable of change in the present based on their imperfect models of the future. Change in simple, mechanistic systems occurs only due to forces acting iteratively on the system’s current state, while change in anticipatory complex systems occurs through both iterative state transitions and from the system’s capacity to respond to anticipatory models. If Rosen’s anticipatory theory of complex systems is correct, implications for improving safety in healthcare organizations are likely to include the following: (1) Greater congruence between the models of the current situation and anticipatory models of future states among clinical team members, and among the clinical team, patient, and family increases the likelihood of attaining preferred outcomes; (2) Inputs from the anticipatory models of clinical team members, patients, and families may be useful for identifying and real time mitigation of some clinical situations in which there is an increased risk of a future serious adverse outcome; (3) Significantly discrepant present-state or anticipatory mental models between clinical team members or between team and patients/families may indicate an increased risk for an adverse outcome; (4) Clinical teams that recognize that disagreements regarding the appropriate care of a patient may indicate an increased risk of an adverse outcome may be able to create better shared present-state and anticipatory mental modes which could help mitigate future risks; and (5) Optimal team functioning should encourage anticipatory inputs from all clinical team members and should include encourage identifying significantly discrepant current state and anticipatory models among clinical team members and between clinical team and patients/families, especially in high-risk situations.

The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.