Systems — Open Access Journal

Inelasticity of demand along with the distributed energy sources and energy market democratization pose significant challenges which have considerable negative impacts on overall grid balance. The need for increased capacity and flexibility in the era of energy market digitalization has introduced new requirements in the energy supply network which could not be satisfied without continuous and costly local power network upgrades. Additionally, with the emergence of Smart Homes (SHs) and Home Energy Management (HEM) systems for monitoring and operating household appliances, opportunities have arisen for automated Demand Response (DR). DR is exploited for the modification of the consumer energy demand, in response to the specific conditions within the electricity system (e.g., peak period network congestion). In order to optimally integrate DR in the broader Smart Grid (SG) system, modelling of the system parameters and safety analysis is required. In this paper, the implementation of STPA (System-Theoretic Process Analysis) structured method, as a relatively new hazard analysis technique for complex systems is presented and the feasibility of STPA implementation for loss prevention on a Demand Response system for home energy management, and within the complex SG context, is examined. The applied method delivers a mechanism useful in understanding where gaps in current operational risk structures may exist. The STPA findings in terms of loss scenarios can be used to generate a variety of safeguards to ensure secure operational control and in implementing targeted strategies through standard approaches of risk assessment. Full article

Human interactions are paramount to the user experience, satisfaction, and risk of user errors. For products, anthropometry has traditionally been used in product sizing. However, structured methods that accurately map static and dynamic capabilities (e.g., functional mapping) of musculoskeletal regions for the conceptualization and redesign of product applications and use cases are limited. The present work aims to introduce and validate the effectiveness of the Interaction Variability method, which maps product components and musculoskeletal regions to determine explicit design parameters through limiting designer variation in the classification of human interaction factors. This study enrolled 16 engineering students to evaluate two series of interactions for (1) water bottle and (2) sunglasses applications enabling method validity and designer consistency assessments. For each interaction series, subjects identified and characterized product applications, components, and human interaction factors. Primary interactions, product mapping, and application identification achieved consensus between ranges of 31.25% and 100.00%, with significance (p < 0.1) observed at consensus rates of ≥75.00%. Significant levels of consistency were observed amongst designers, for at least one measure in all phases except anthropometric mapping for the sunglasses application indicating method effectiveness. Interaction variability was introduced and validated in this work as a standardized approach to identify, define, and map human and product interactions, which may reduce unintended use cases and user errors, respectively, in consumer populations. Full article

This paper reflects on a seminal work in the history of AI and representation: Rodney Brooks’ 1991 paper Intelligence without representation. Brooks advocated the removal of explicit representations and engineered environments from the domain of his robotic intelligence experimentation, in favour of an evolutionary-inspired approach using layers of reactive behaviour that operated independently of each other. Brooks criticised the current progress in AI research and believed that removing complex representation from AI would help address problematic areas in modelling the mind. His belief was that we should develop artificial intelligence by being guided by the evolutionary development of our own intelligence and that his approach mirrored how our own intelligence functions. Thus, the field of behaviour-based robotics emerged. This paper offers a historical analysis of Brooks’ behaviour-based robotics approach and its impact on artificial intelligence and cognitive theory at the time, as well as on modern-day approaches to AI. Full article

Modeling human decision-making is difficult. Decision-makers are typically primed with unique biases that widen the confidence interval of judgment. Therefore, it is important that the human process in the system being modeled is designed to alleviate damaging biases and assumptions in an effort to increase process consistency between decision-makers. In this experiment, it is hypothesized that coupling specific decision-facilitation methods with a specific scale range will affect the consistency between decision-makers. This article presents a multiphase experiment that examines a varying presentation mode as well as scale range to determine how value is determined in subsequent pairwise comparisons of alternatives against specific requirements. When considering subject value ratings of the expected rank order of alternative subgroups (indicating strong criteria independence), results show that subjects used consistent comparison ratios regardless of the scale range. Furthermore, when comparing the subgroups of expected rank order responses to the subgroups of biased responses, although ratios were different, the same general trend of comparison existed within subgroups. Providing evidence that careful selection of the presentation mode can facilitate more consistent value comparisons between compatible decision-makers allows for the identification of and adjustment of disparities due to bias and potential lack of incremental scaling detail. Furthermore, by creating decision processes that render more consistent cognitive behavior between decision-makers, tighter confidence intervals can be obtained, and critical assumptions can be validated. Full article

Energy efficiency, indoor environmental quality, and comfort in public buildings has received increasing attention in recent years as it can contribute to maintaining safety conditions and to the reduction of conventional fuels consumption, energy costs for building owners, and greenhouse gas emissions. People are an integral part of any building energetic ecosystem as, according to some estimates, they spend a great part of their life in indoor spaces. On one side, occupants are responsible for the energy consumption of the building and for this reason the “psychology of energy saving” has received attention since the 70s up to recent results. On the other hand, strategies for energy efficiency should not jeopardize occupants’ health and quality of life. While general awareness of the value of environmental variables has increased in the last few years, this interest has recently been further exacerbated by the spreading of the well-known COVID-19 pandemic. In fact, as most countries have started planning post-lock-down activities, there is a growing concern regarding how social distancing measures can be enforced in shared buildings and strict indoor air quality control can prevent airborne virus transmission in crowded spaces. The paper discusses the perspectives of increasing the level of social interaction of building users through the systematic use of Information and Communication Technologies (ICT), and in particular, some specific platforms. The ICT system, taking information from the occupants in a concerted way, can be an important instrument to collect data, coming both from physical sensors and from people to develop a multi-objective control strategy for the Heating, Ventilation, and Air Cooling (HVAC) systems in order to obtain energy savings whilst balancing user comfort and healthy conditions. Full article

Open-source software (OSS) is a key aspect of software creation. However, little is known about programmers’ decisions to trust software from OSS websites. The current study emulated OSS websites and manipulated reputation and performance factors in the stimuli according to the heuristic-systematic processing model. We sampled professional programmers—with a minimum experience of three years—from Amazon Mechanical Turk (N = 38). We used a 3 × 3 within-subjects design to investigate the relationship between OSS reputation and performance on users’ time spent on code, the number of interface clicks, trustworthiness perceptions, and willingness to use OSS code. We found that participants spent more time on and clicked the interface more often for code that was high in reputation. Meta-information included with OSS tools was found to affect the degree to which computer programmers interact with and perceive online code repositories. Furthermore, participants reported higher levels of perceived trustworthiness in and trust toward highly reputable OSS code. Notably, we observed fewer significant main effects for the performance manipulation, which may correspond to participants considering performance attributes mainly within the context of reputation-relevant information. That is, the degree to which programmers investigate and then trust OSS code may depend on the initial reputation ratings. Full article

There are inherent difficulties in designing an effective Human–Machine Interface (HMI) for a first-of-its-kind system. Many leading cognitive research methods rely upon experts with prior experiences using the system and/or some type of existing mockups or working prototype of the HMI, and neither of these resources are available for such a new system. Further, these methods are time consuming and incompatible with more rapid and iterative systems development models (e.g., Agile/Scrum). To address these challenges, we developed a Wargame-Augmented Knowledge Elicitation (WAKE) method to identify information requirements and underlying assumptions in operator decision making concurrently with operational concepts. The developed WAKE method incorporates naturalistic observations of operator decision making in a wargaming scenario with freeze-probe queries and structured analytic techniques to identify and prioritize information requirements for a novel HMI. An overview of the method, required apparatus, and associated analytical techniques is provided. Outcomes, lessons learned, and topics for future research resulting from two different applications of the WAKE method are also discussed. Full article

Systems engineering practices in the maritime industry and the Navy consider operational availability as a system attribute determined by system components and a maintenance concept. A better understanding of the risk attitudes of system operators and maintainers may be useful in understanding potential impacts the system operators and maintainers have on operational availability. This article contributes to the literature a method that synthesizes the concepts of system reliability, and operator and maintainer risk attitudes to provide insight into the effect that risk attitudes of systems operators and maintainers have on system operational availability. The method consists of four steps providing the engineer with a risk-attitude-adjusted insight into the system’s potential operational availability. Systems engineers may use the method to iterate a system’s design or maintenance concept to improve expected operational availability. If it is deemed necessary to redesign a system, systems engineers will likely choose new system components and/or alter their configuration; however, redesign is not limited to physical alteration of the system. Several other options may be more practical depending the system’s stage in the life cycle to address low risk-adjusted operational availability such as changes to maintenance programs and system supportability rather than on component and system reliability. A simple representative example implementation is provided to demonstrate the method and discussion of the potential implications for Navy ship availability are discussed. Potential future work is also discussed. Full article

We discuss an approach to using the event study, a common experimental design in the social sciences, to parameterize delays and develop other insights into system structure. We show a step-by-step process for undertaking a delay event study, discuss some of the conceptual reasons that this provides information about the delay, and illustrate the process for a typical example. We find evidence that school funding changes following court orders do not adjust quickly, and likely follow a higher-order, as opposed to a first-order, delay process. Our tests also suggest that school district budget makers appear to forecast revenue pessimistically, contributing an additional source of delay to the system. Full article

The current pandemic is a great challenge for several research areas. In addition to virology research, mathematical models and simulations can be a valuable contribution to the understanding of the dynamics of the pandemic and can give recommendations to physicians and politicians. Based on actual data of people infected with COVID-19 from the European Center for Disease Prevention and Control (ECDC), input parameters of mathematical models will be determined and applied. These parameters will be estimated for the UK, Italy, Spain, and Germany and used in an $SIR$ -type model. As a basis for the model’s calibration, the initial exponential growth phase of the COVID-19 pandemic in the named countries is used. Strategies for the commencing and ending of social and economic shutdown measures are discussed. Full article

Systems thinking (ST) is an interdisciplinary domain that offers different ways to better understand the behavior and structure of a complex system. Over the past decades, several publications can be identified in academic literature, focusing on different aspects of systems thinking. However, two critical questions are not properly addressed in the extant body of ST literature: (i) How to conduct the content analysis exclusively to derive the prominent statistics (i.e., influential journals, authors, affiliated organizations and countries) pertaining to the domain of ST? (ii) How to get better insights regarding the current and emerging trends that may evolve over time based on the existing body of ST literature? To address these gaps, the aim of this research study is to provide a comprehensive insight into the domain of systems thinking through bibliometric and network analysis. Beginning with over 6000 accumulated publications, the analysis narrowed down to 626 prominent articles with proven influence published over the past three decades. Leveraging rigorous bibliometric tools analysis, this research unveils the influential authors, leading journals and top contributing organizations and countries germane to the domain of systems thinking. In addition, citation, co-citation and page rank analysis used to rank top influential articles in the area of systems thinking. Finally, with the aid of the network analysis, key clusters in the existing literature are identified based on the research areas of systems thinking. The findings of this research will serve as a bluebook for practitioners and scholars to conduct future research within systems thinking context. Full article

The shift towards Product-Service Systems (PSS) stresses the need to embed new and unique capabilities in Decision Support Systems, with the aim of helping the engineering team in handling the pool of information and knowledge available during decision events. Emerging from a multiple case study in the Swedish manufacturing industry, this paper describes the development of the Model-Driven Decision Arena (MDDA), an environment for collaborative decision-making that focuses on the early design phases of PSS. Based on the findings from multiple case studies, this paper illustrates the main goals of the MDDA, detailing its main functions, its physical environment, and its software architecture and models. This paper demonstrates the use of the MDDA in a case study related to the development of an asphalt compactor, presenting and discussing the results of verification activities conducted with industrial practitioners on the current MDDA prototype. Full article

Governments around the world have introduced a number of stringent policies to try to contain COVID-19 outbreaks, but the relative importance of such measures, in comparison to the community response to these restrictions, the amount of testing conducted, and the interconnections between them, is not well understood yet. In this study, data were collected from numerous online sources, pre-processed and analysed, and a number of Bayesian Network models were developed, in an attempt to unpack such complexity. Results show that early, high-volume testing was the most crucial factor in successfully monitoring and controlling the outbreaks; when testing was low, early government and community responses were found to be both critical in predicting how rapidly cases and deaths grew in the first weeks of the outbreak. Results also highlight that in countries with low early test numbers, the undiagnosed cases could have been up to five times higher than the officially diagnosed cases. The conducted analysis and developed models can be refined in the future with more data and variables, to understand/model potential second waves of contagions. Full article

COVID-19 is a wicked problem for policy makers internationally as the complexity of the pandemic transcends health, environment, social and economic boundaries. Many countries are focusing on two key responses, namely virus containment and financial measures, but fail to recognise other aspects. The systems approach, however, enables policy makers to design the most effective strategies and reduce the unintended consequences. To achieve fundamental change, it is imperative to firstly identify the “right” interventions (leverage points) and implement additional measures to reduce negative consequences. To do so, a preliminary causal loop diagram of the COVID-19 pandemic was designed to explore its influence on socio-economic systems. In order to transcend the “wait and see” approach, and create an adaptive and resilient system, governments need to consider “deep” leverage points that can be realistically maintained over the long-term and cause a fundamental change, rather than focusing on “shallow” leverage points that are relatively easy to implement but do not result in significant systemic change. Full article

Water security plays a crucial role in maintaining livelihoods, especially emerging economies. In Malaysia, understanding the inter-relationships of water within the water-energy-food (WEF) nexus is at its infancy. This paper investigates the interactions of the water sector with energy sector in Malaysia, through the lenses of WEF nexus, using system dynamics. The first part of the research involves qualitative interviews with key stakeholders in the water sectors, which provides validation for the initial causal loop relationships built and qualitative inputs of the water-energy nexus through the lenses of the water sector. The second part of the research is a quantitative simulation of stock and flow based on four carefully designed scenarios revolving around Malaysian water security. Key findings include an apparent disconnect between the states and federal governments in managing water supply, poor economic sustainability of the water supply and services industry, and significant energy use in the water sector. On the other hand, environmental impacts stemming from the water sector is minimal. Streamlining water governance and revising water tariffs have thus been suggested as policy recommendations, where their implementation could propagate into downstream benefits for the energy sector. Full article

Korea initiated a new experiment, called a dynamic response system for open democratic societies as a principle to respond to the novel coronavirus (COVID-19). The global pandemic of COVID-19 led to a surge in demand for healthcare medical masks and respirators, and strained the global supply chain of mask production and distribution systems. This study provides a systemic view of critical personal protective equipment for both healthcare staff and the public to stop the spread of COVID-19. This study investigates the dynamic response system of healthcare mask production to the coronavirus and discusses lessons learned in view of systems thinking. The study shows that it is critical to developing a quick and dynamic response system to the evolving market conditions with flexible and agile operations. Visibility with transparency with information sharing with the public is also critical under global pandemic. Due to the shortage of mask supply, smart consumption is required along with collaboration with public and private sectors, as well as global organizations. Democratic leadership and a well-prepared strategic plan for long-term period are essential to the open society to prepare the global pandemic in the future. This study serves as a benchmark for dynamic and timely responses to the global pandemic. Full article

The simulation of population dynamics and social processes is of great interest in nonlinear systems. Recently, many scholars have paid attention to the possible applications of population dynamics models, such as the competitive Lotka–Volterra equation, in economic, demographic and social sciences. It was found that these models can describe some complex behavioral phenomena such as marital behavior, the stable marriage problem and other demographic processes, possessing chaotic dynamics under certain conditions. However, the introduction of external factors directly into the continuous system can influence its dynamic properties and requires a reformulation of the whole model. Nowadays most of the simulations are performed on digital computers. Thus, it is possible to use special numerical techniques and discrete effects to introduce additional features to the digital models of continuous systems. In this paper we propose a discrete model with controllable phase-space volume based on the competitive Lotka–Volterra equations. This model is obtained through the application of semi-implicit numerical methods with controllable symmetry to the continuous competitive Lotka–Volterra model. The proposed model provides almost linear control of the phase-space volume and, consequently, the quantitative characteristics of simulated behavior, by shifting the symmetry of the underlying finite-difference scheme. We explicitly show the possibility of introducing almost arbitrary law to control the phase-space volume and entropy of the system. The proposed approach is verified through bifurcation, time domain and phase-space volume analysis. Several possible applications of the developed model to the social and demographic problems’ simulation are discussed. The developed discrete model can be broadly used in modern behavioral, demographic and social studies. Full article

This work studies a hybrid manufacturing–remanufacturing system with a sorting line and disposal. In particular, it models a company that collects used product, remanufactures returned products that have been evaluated as suitable to be recovered, and manufactures new products to satisfy customer demand. Specifically, the system is modeled as a multilevel inventory system, with three types of stock (used products inventory, recoverable inventory, and serviceable inventory), each characterized by an inventory holding cost, and three limited capacity resources: a sorting line, which enables the company to distinguish those returns that are remanufacturable from those that are not; a remanufacturing line to carry out operations on sorted remanufacturable returns; and a manufacturing line to produce new products in order to satisfy customer demand. Each resource is characterized by a setup cost, as well as a constant production rate, while each type of stock is associated with an inventory holding cost. The aim of the paper is to develop a model for the considered production system in order to minimize the setup and inventory holding costs. In particular, the objective is to evaluate the behavior of a controllable disposal rate with the minimization of the total cost function, by considering the effect on the remanufacturing and manufacturing lines. Full article

Geometric-Zeno behaviour is a highly challenging problem in the analysis (including simulation) of hybrid systems. Geometric-Zeno can be defined as an infinite number of discrete mode switches in a finite time interval. Typically, for hybrid models exhibiting geometric-Zeno, the numerical simulation either halts or produces false results, because an infinite number of discrete events occur in a given simulation time-step. In this paper, we provide formal methods for regularization of geometric-Zeno behaviour by using a non-standard analysis. In particular, we provide formal conditions for the existence of geometric-Zeno in hybrid systems, and we propose methods to allow geometric-Zeno executions to be continued beyond geometric-Zeno limit points. The concepts are illustrated with a case study throughout the paper. Full article