Robust design of complex socio-technical systems against seasonal effects: a network motif-based approach

Seasonal effects can significantly impact the robustness of socio-technical systems (STS) to demand fluctuations. There is an increasing need to develop novel design approaches that can support capacity planning decisions for enhancing the robustness of STS against seasonal effects. This paper proposes a new network motif-based approach to supporting capacity planning in STS for an improved seasonal robustness. Network motifs are underlying nonrandom subgraphs within a complex network. In this approach, we introduce three motif-based metrics for system performance evaluation and capacity planning decision-making. The first one is the imbalance score of a motif (e.g., a local service network), the second one is the measurement of a motif’s seasonal robustness, and the third one is a capacity planning decision criterion. Based on these three metrics, we validate that the sensitivity of STS performance against seasonal effects is highly correlated with the imbalanced capacity between service nodes in an STS. Correspondingly, we formulate a design optimisation problem to improve the robustness of STS by rebalancing the resources at critical service nodes. To demonstrate the utility of the approach, a case study on Divvy bike-sharing system in Chicago is conducted. With a focus on the size-3 motifs (a subgraph consisting three docked stations), we find that there is a significant correlation between the difference of the number of docks among the stations in a motif and the return/rental performance of such a motif against seasonal changes. Guided by this finding, our design approach can successfully balance out the number of docks between those stations that have caused the most severe seasonal perturbations. The results also imply that the network motifs can be an effective local structural representation in support of STS robust design. Our approach can be generally applied in other STS where the system performances are significantly impacted by seasonal changes, for example, supply chain networks, transportation systems and power grids.

Considerations of the Mental Workload in Socio-Technical Systems in the Manufacturing Industry

As cognitive tasks have displaced physical tasks in today's manufacturing industry, this sector can demand high levels of mental workload from workers. In certain situations, there is a high cognitive load, which affects operators reducing their attention to the task and causing them mental fatigue and distractions, resulting in errors that generate economic costs or even injuries to workers. This literature review aims to provide a comprehensive understanding the use of mental workload in the manufacturing sector. The methodology consisted of conducting a search in four databases. In the search, a combination of keywords was used, classifying each journal according to the mental workload evaluation means, the type of evaluation, and the area of application. Articles not focusing on the manufacturing area were discarded. Of the total of 3839 articles found, 12 have been selected. Regarding the methods used for mental load assessment, the analytic techniques were found to be the most frequently used.

Artificial Intelligence and Threat to Humanity

AI is growing in popular technology with various uses can be seen in many aspects of life. AI has many positive effects and creates social benefits. AI applications can improve health and living conditions, facilitate justice, create wealth, enhance public safety, and reduce the impact of human activities on the environment and climate (Montreal Declaration 2018). AI is a tool that can help people do their jobs faster and better, creating many benefits. But, beyond that, AI can also facilitate new tasks, for example by analyzing research data on an unprecedented scale, thus creating an expectation of scientific knowledge. can be beneficial in all aspects of life. In this paper we are describing negative effects of AI. Keywords: Artificial intelligence, ML, Artificialgeneral intelligence · Socio-technical systems

On the classification of motive power failures

The Aim of the article is to develop a motive power failure classification to enable substantiated definition of dependability requirements for motive power as a part of a railway transportation system, as well as for organizing systematic measures to ensure a required level of its dependability over the life cycle. Methods. The terminology of interstate dependability-related standards was analysed and the two classifications used by OJSC “RZD” for estimating the dependability of technical systems and motive power were compared. The dependability of railway transportation systems is studied using structural and logical and logical and probabilistic methods of dependability analysis, while railway lines are examined using the graph theory and the Markov chains. Results. An analysis of the existing failure classifications identified shortcomings that prevent the use of such classifications for studying the structural dependability of such railway transportation systems as motive power. A classification was developed that combines two failure classifications (“category-based” for the transportation process and technical systems and “type-based” for the motive power), but this time with new definitions. The proposed classification of the types of failures involves stricter definitions of the conditions and assumptions required for evaluating the dependability and technical condition of an item, which ensures correlation between the characteristics of motive power and its dependability throughout the life cycle in the context of the above tasks. The two classifications could be used simultaneously while researching structural problems of dependability using logical and probabilistic methods and Markov chains. The developed classification is included in the provisions of the draft interstate standard “Dependability of motive power. Procedure for the definition, calculation methods and supervision of dependability indicators throughout the life cycle” that is being prepared by JSC “VNIKTI” in accordance with the OJSC “RZD” research and development plan. Conclusion. The article’s findings will be useful to experts involved in the evaluation of motive power dependability.

Assessment of the Economic Efficiency of Training Complex System Operators

The possible ways of economic evaluation of the effectiveness of training operators to manage complex technical systems are analyzed. The variants of evaluation are considered, taking into account the achievement of a given level of reliability when performing management tasks, the professional suitability of operators for this type of activity based on their individual characteristics and the characteristics of the tasks being solved.