Identifying Key Relationships between Nation-State Cyberattacks and Geopolitical and Economic Factors: A Model

Nation-state cyberattacks, and particularly Advanced Persistent Threats (APTs), have rocketed in the last years. Their use may be aligned with nation-state geopolitical and economic (GPE) interests, which are key for the underlying international relations (IRs). However, the interdependency between APTs and GPE (and thus IRs) has not been characterized yet and it could be a steppingstone for an enhanced cyberthreat intelligence (CTI). To address this limitation, a set of analytic models are proposed in this work. They are built considering 234M geopolitical events and 306 malicious software tools linked to 13 groups of 7 countries between 2000 and 2019. Models show a substantial support for launched and received cyberattacks considering GPE factors in most countries. Moreover, strategic issues are the key motivator when launching APTs. Therefore, from the CTI perspective, our results show that there is a likely cause-effect relationship between IRs (particularly GPE relevant indicators) and APTs.

Regular graph-based free route flight planning approach

Purpose>The purpose of this study is to provide an alternative graph-based airspace model for more effective free-route flight planning.Design/methodology/approach>Based on graph theory and available data sets describing airspace, as well as weather phenomena, a new FRA model is proposed. The model is applied for near to optimal flight route finding. The software tool developed during the study and complexity analysis proved the applicability and timed effectivity of the flight planning approach.Findings>The sparse bidirectional graph with edges connecting only (geographically) closest neighbours can naturally model local airspace and weather phenomena. It can be naturally applied to effective near to optimal flight route planning.Research limitations/implications>Practical results were acquired for one country airspace model.Practical implications>More efficient and applicable flight planning methodology was introduced.Social implications>Aircraft following the new routes will fly shorter trajectories, which positively influence on the natural environment, flight time and fuel consumption.Originality/value>The airspace model proposed is based on standard mathematical backgrounds. However, it includes the original airspace and weather mapping idea, as well as it enables to shorten flight planning computations.

A Description of Data Handling Practices and Software Tools Developed by the Boston Children's Hospital Echo Core Laboratory

Ultrasound 'Echocardiogram (echo)' images generated by commercial scanners are non-invasive, economical, and have therefore become an important clinical and research tool for cardiovascular disease. The Boston Children's Hospital (BCH, USA) cardiology department has developed echo image handling processes and software tools to simplify and manage the flow of echo data from sites participating in multi-center research studies. With frequent needs to correlate echocardiographic findings with surgical outcomes and more recently, better understand the acute and long-term effects of the SARS-CoV-2 pandemic on the heart in a multiinstitutional collaborative [1], the need for a central corelab for image review and reporting has spurred the development of new software tools that seamlessly prepare, transmit and measure echocardiographic images and generate reports formatted to merge easily with clinical databases. In this paper we provide a descriptive guide to these software tools, and offer suggested approaches to data preparations that can simplify corelab processing.

Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia

The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it requires engaging with our environments, analyzing them, and making sustainable decisions regulated by triple bottom line (TBL). Poor healthcare systems affect individuals, societies, the planet, and economies. This paper proposes a data-driven artificial intelligence (AI) based approach called Musawah to automatically discover healthcare services that can be developed or co-created by various stakeholders using social media analysis. The case study focuses on cancer disease in Saudi Arabia using Twitter data in the Arabic language. Specifically, we discover 17 services using machine learning from Twitter data using the Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-services, namely, Prevention, Treatment, Psychological Support, Socioeconomic Sustainability, and Information Availability. Subsequently, we show the possibility of finding additional services by employing a topical search over the dataset and have discovered 42 additional services. We developed a software tool from scratch for this work that implements a complete machine learning pipeline using a dataset containing over 1.35 million tweets we curated during September–November 2021. Open service and value healthcare systems based on freely available information can revolutionize healthcare in manners similar to the open-source revolution by using information made available by the public, the government, third and fourth sectors, or others, allowing new forms of preventions, cures, treatments, and support structures.

The Complex Systems for Conflict Interaction Modelling to Describe a Non-Trivial Epidemiological Situation

This study investigates a complex system that describes a non-trivial epidemiological model with integrated internal conflict (interregional migration) on the example of cyclic migration using the software. JetBrains PyCharm Community Edition 2020.3.3, a free and open-source integrated development environment (IDE) in the Python programming language, was chosen as the software development tool. The Matplotlib 3.5 library was used to display the modelling results graphically. The integration of internal conflict into the model revealed significant and notable changes in its behavior. This study’s results prove that not only the characteristics of the interaction factors but also the size of the values determine the direction of migration concerning relation to competitors.

FROM THE CHAIRMAN AND EXECUTIVE EDITOR

In the second article, Challenges of Adopting DevOps for Combat Systems Development Environment, the authors, Andrew W. Miller, Ronald E. Giachetti, and Douglas L. Van Bossuyt, interviewed multiple subject matter experts in the Navy and DoD to identify some of the challenges and obstacles to adapting DevOps to the Navy acquisition process. Authors Tom Ahn and Amilcar A. Menichini examine the effect of the pandemic on DoD worker retention rates in their article, Optimal Talent Management of the Acquisition Workforce in Response to COVID-19: Dynamic Programming Approach. The results of their research highlight ways that the DoD can take advantage of negative impacts to the civilian labor market in the short term as well as reforms that need to be made to retain high-quality DoD workers long term.