This article supports SDG 13 and 9 by providing exploring the estimation of the role of the studied species as sinks of atmospheric carbon.
This paper show the mathematical and theoretical background of the machine learning algorithm used in this work, the LSTM. The data used are described and the methodology of framework is presented. It shows the predictions results based on LSTM and comparisons with ERA5 and buoy observations.
This Study explores the racial disparities that exist in the emergency departments of 4 hospitals, when they are most prevalent, and how patients' sociodemographic characteristics impact image acquisition time, raising awareness for SDGs 3, 9 and 10.
The Internet of Things (IoT) has revolutionized the traditional healthcare systems into intelligent system by allowing remote access and continuous monitoring of patient data. Specifically, first a novel scalable blockchain architecture is proposed to ensure data integrity and secure data transmission by leveraging Zero Knowledge Proof (ZKP) mechanism. Then, BDSDT integrates with the off-chain storage InterPlanetary File System (IPFS) to address difficulties with data storage costs and with an Ethereum smart contract to address data security issues.
Evaluating the bias and fairness of ML models has drawn much attention in the machine learning and statistics community. Researchers have proposed methods to assess and mitigate the bias for various applications that could adversely affect underrepresented groups, like recidivism prediction, credit risk prediction, and income prediction.
Our research explores how Stakeholder Capitalism can contribute to global governance to achieve all the 17 SDGs. The main findings revealed that Stakeholder Capitalism and its principles are favorable to foster a friendly environment for achieving most of the SDGs and can contribute to global governance in achieving mainly the SDGs 8, 9, and 17. However, Stakeholder Capitalism literature is incipient for the SDGs 6, 14, and 15, needing further research development by considering non-human stakeholders and the environment.
This article supports SDG 3 and 9 by describing a survey of health-care workers in New Zealand on the acceptability of PPE disinfection and reuse to reduce waste and increase availability and sustainability; the survey that this practice was common and had high acceptability, contingent on availability of scientific evidence in support of the disinfection process, and workers' trust in the organisation undertaking the disinfection
This chapter advances the UN SDG goals 8, 9, and 11 by exploring how AI can be utilized by city officials to improve quality of life in sustainable cities.
An investigation supporting SDGs 7 and 13, based in Ghana, into the possibility of using slaughterhouse wastes as a source of renewable energy through biogas technology. The researchers concluded that 'Ghana generates significant amount of slaughterhouse waste each year that can be processed using AD [anaerobic digestion] for energy and electricity production to supplement the country's electricity needs, while reducing GHG emissions'.
We observe the link between Artificial Intelligence (AI) and Sustainable Development Goals (SDGs). We use automated methodologies to find insights and overlaps between AI and the SDGs. AI-Ethics frameworks need to give more attention to Society and Environment areas. Inclusive action is needed to balance the efforts for solving SDGs by using AI.SDGs 13, 14, and 15 (all related to the Environment area) are not sufficiently addressed.
