Study on Dynamic Change of Land Usage in Hongta District Based on Sentinel-2

This work utilizes Sentinel-2A L1C remote sensing photographs from the years 2018, 2020, and 2022 to identify the different land use categories in the study area using the support vector machine (SVM) technique. The accuracy of categorization is greater than 90%. This research explores four factors of the dynamic change in land use in Hongta District from 2018 to 2022: the proportion of various types of land;the extent of something like the changing land usage;land use transfer;and the dynamic degree of the change in land use. According to the study's results, the proportion of cultivated and grassland land grew, while the quantity of barren and construction land fell by 1.90 percent, 0.03 percent, and 0.69 percent, respectively. The water system land portion of total area increased by 2.58 percent and 0.13 percent, respectively. After comparing the two research periods, the entire dynamic degree of the second stage is determined to be 3.5 percent lower than that of the first stage, and the pace of land use change is quite sluggish, which may be associated with the worldwide COVID-19 outbreak in 2020. The outcomes of the research may give the natural resources department the knowledge it needs to manage land resources properly. © 2023 SPIE.

A hybrid approach based on dynamic trajectories to predict mortality in COVID-19 patients upon steroids administration

Since the World Health Organization (WHO) has declared Artificial Intelligence (AI) as a powerful tool in the fight against COVID-19, multiple studies have been launched aiming to shed light into risk factors for ICU admission and mortality. None of the existing studies, however, have captured the dynamic trajectories of hospitalized COVID-19 patients who receive steroids nor have explored trajectory-based mortality indicators. In this work, we present a novel, hybrid approach to address this need. Latent Growth Mixture Modelling (LGMM) was used to analyze the trajectories of patients who received steroids. The patients were then grouped into clusters based on the similarity of their dynamic trajectories. State-of-the art machine learning classifiers are trained on the original dataset with and without dynamic trajectories to assess whether their inclusion can enhance the prediction of mortality. Our results highlight the importance of trajectories for predicting mortality in patients who receive steroids yielding 4% and 5% increase in the sensitivity (0.84) and specificity (0.85). The FiO2 and percentage of neutrophils at day 5, along with the percentage of lymphocytes at day 7, were identified as the main causes for mortality in patients who receive steroids, where the SatO2 levels showed significant alterations in the dynamic trajectories. © 2022 IEEE.

RESILIENCE, PEOPLE AND INFORMATION, A TRIANGLE TO BUILD SUSTAINABILITY

Digital revolutions and developments have been changing the way we work, socialize and experience the world. In our complex reality dynamic changes occur with an increasing frequency, where the role of IT is obvious. The COVID pandemic highlighted this development even more and made us realize that the old ways of working are no longer valid. In this conceptual paper we sketch different scientific views to offer practical solutions to deal with challenges. We focus on dynamic developments on concepts from ecology and economics, identify some traps and link the insights to management, leadership, teams and the requirements for a successful cooperation. Our goal is to identify the most crucial elements of sustainability: resilience, people and information, offer organizations developing solutions using the Adaptive Cycle of Resilience and help the reader to develop understanding social responsibility towards resilience and sustainability. © Proceedings of the 2021 AIS SIGED International Conference on Information Systems Education and Research.

Research on dynamic coalition stability of mask production under COVID-19 epidemic

Based on evolutionary game and catastrophe theory, the stability of dynamic coalition of mask production is explored. This research introduces the Gaussian White noise and a Itô stochastic differential equation to develop dynamical equation. Then, probability density function is introduced to build the catastrophe model. Finally, some numerical simulations are given to explore the influence of excess return, default cost and initial cooperation probability. The results show: 1) Catastrophic change occurs suddenly when parameters cross the borderline of bifurcation aggregation;2) The catastrophic change occurs due to external disturbance when parameters are inside the bifurcation aggregation which is easy to recover;3) The excess return affects negatively, and the default cost and the initial cooperation probability affect positively on the stability of dynamic coalition. This research integrates evolutionary game and catastrophe theory and provide a new idea for dynamic coalition research;supports the establishment of mask production dynamic coalition and implementation for unconventional control measures under the COVID-19 epidemic. © 2021, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.