The combat system-of-systems in high-tech informative warfare consists of different types of combat systems connected via multiple interconnections, which can be abstracted as types of complex heterogeneous networks. Research on the functional robustness of heterogeneous combat networks (HCNs) is of significant military value for optimizing operation process planning and for improving network survivability in complex electromagnetic battle fields. This study presents an integrated framework, known as the HCN functional robustness (HCNFR) framework to measure the functional robustness of HCNs under various attacking strategies. Specifically, a heterogeneous network model is introduced to characterize HCNs considering different types of functional entities and information flows. Based on this setup, the rescaled operational capability index (ROCI) is first proposed to evaluate the functional robustness of HCNs, and the criterion for functional disintegration of HCNs is established by summing the values of ROCI during the attacking process. Finally, the reliability and effectiveness of HCNFR are illustrated with an empirical case study. The results provide useful insights for operational guidance and design of a more functional and robust combat system-of-systems.

A central question in the science of science concerns how to develop a quantitative understanding of the evolution and impact of individual careers. Over the course of history, a relatively small fraction of individuals have made disproportionate, profound, and lasting impacts on science and society. Despite a long-standing interest in the careers of scientific elites across diverse disciplines, it remains difficult to collect large-scale career histories that could serve as training sets for systematic empirical and theoretical studies. Here, by combining unstructured data collected from CVs, university websites, and Wikipedia, together with the publication and citation database from Microsoft Academic Graph (MAG), we reconstructed publication histories of nearly all Nobel prize winners from the past century, through both manual curation and algorithmic disambiguation procedures. Data validation shows that the collected dataset presents among the most comprehensive collection of publication records for Nobel laureates currently available. As our quantitative understanding of science deepens, this dataset is expected to have increasing value. It will not only allow us to quantitatively probe novel patterns of productivity, collaboration, and impact governing successful scientific careers, it may also help us unearth the fundamental principles underlying creativity and the genesis of scientific breakthroughs.

Modern military operations in high-tech information warfare settings are dynamic processes involving various types of combat systems connected via multiple channels, which can be abstracted as a type of complex temporal combat network (TCN). The equipment contribution analysis in TCNs is of significant military value for optimizing operation process planning and improving network resilience in complex electromagnetic battlefields. This paper presents an integrated framework called capability oriented equipment contribution analysis (CECA) to analyze key equipment in TCNs. Specifically, a temporal network model is proposed to characterize TCNs by considering their dynamic nature and the heterogeneity capabilities of different types of functional entities during military operations. Based on this model, an operation capability contribution index is proposed to measure the contribution of each piece of equipment involved in executing operational tasks. Finally, the reliability and effectiveness of the CECA are demonstrated based on a TCN case study. This paper provides a detailed and precise quantitative analysis of the equipment contributions in TCNs, which yields useful insights for operation guidance and designing a more resilient combat system-of-systems.

Complex systems widely exist in nature and human society. There are complex interactions between system elements in a complex system, and systems show complex features at the macro level, such as emergence, self-organization, uncertainty, and dynamics. These complex features make it difficult to understand the internal operation mechanism of complex systems. Networked modeling of complex systems is a favorable means of understanding complex systems. It not only represents complex interactions but also reflects essential attributes of complex systems. This paper summarizes the research progress of complex systems modeling and analysis from the perspective of network science, including networked modeling, vital node analysis, network invulnerability analysis, network disintegration analysis, resilience analysis, complex network link prediction, and the attacker-defender game in complex networks. In addition, this paper presents some points of view on the trend and focus of future research on network analysis of complex systems.

The combat system-of-systems (CSoSs) in high-tech information warfare, composed of different types of combat systems connected through multiple interconnections, can be abstracted as a type of complex heterogeneous network. Research on the disintegration of the operational capability of a heterogeneous combat network (HCN) is of significant military value for optimizing the planning of operation process and improving network survivability in a complex electromagnetic battlefield. Accordingly, this paper presents an integrated framework called HCN operational capability disintegration based on link prediction (OCDLP) for modeling and solving the disintegration problem regarding the operational capability of an HCN. More specifically, a heterogeneous network model of a combat network under incomplete information is first established, considering different types of functional entities and information flows. Based on this model, a link prediction model is then applied to recover the original combat network structure while taking advantage of the observed information. Next, a disintegration evaluation metric of the operational capability of an HCN is elicited to evaluate the attack efficiency after a link prediction. Last, the reliability and effectiveness of the OCDLP are illustrated through a case study. The results provide useful insight into the operation guidance and design of a more resilient CSoSs.