Article
Geosciences, Multidisciplinary
Ehsan Shakeri, Bela Vizvari, Ramtin Nazerian
Summary: This paper reviews, compares, and analyzes the legal and institutional frameworks of Disaster Management (DM) systems in India and Nigeria, finding that India has developed a more effective system compared to Nigeria. However, both countries face challenges in mobilizing and managing DM funds due to a lack of transparency. The study also highlights the focus on natural disasters and the lack of emphasis on man-made hazards in both countries' DM systems.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Construction & Building Technology
Tarik Lahna, Bernard Kamsu-Foguem, Henry Fonbeyin Abanda
Summary: Maintenance in airport infrastructures has attracted scientists and practitioners worldwide due to its critical function. Maintenance costs account for a significant part of airport infrastructure operating costs. Therefore, the use of maintenance management methods and tools, such as BIM, is essential to detect and solve potential failures before they occur. This study conducted a bibliometric analysis to evaluate current research levels and identify potential future research avenues in airport infrastructure maintenance.
JOURNAL OF BUILDING ENGINEERING
(2023)
Review
Green & Sustainable Science & Technology
Sheikh Kamran Abid, Noralfishah Sulaiman, Shiau Wei Chan, Umber Nazir, Muhammad Abid, Heesup Han, Antonio Ariza-Montes, Alejandro Vega-Munoz
Summary: Enhancement of technical and methodological approaches in hazards and disaster research is crucial in disaster management. The applications of artificial intelligence, such as tracking, geospatial analysis, machine learning, etc., have significant implications for studying disasters. Social science researchers have utilized various technologies and methods in interdisciplinary ways to examine disasters. Integrating geographic information systems and remote sensing into disaster management can improve planning, analysis, and recovery operations.
Article
Information Science & Library Science
Nayomi Kankanamge, Tan Yigitcanlar, Ashantha Goonetilleke
Summary: The study found that younger generations appreciate the opportunities created by AI in disaster management, those with tertiary education understand the benefits of AI better, and public sector administrative and safety workers value the contributions of AI in disaster management.
TELEMATICS AND INFORMATICS
(2021)
Article
Biochemistry & Molecular Biology
Sandipan Paul Arnab, Md Ruhul Amin, Michael DeGiorgio
Summary: Natural selection leaves a spatial pattern along the genome, and considering the genomic spatial distribution of multiple summary statistics allows for distinguishing patterns of natural selection from neutrality. Various methods have been developed to analyze genomic spatial distributions across summary statistics using machine learning and deep learning architectures. In this study, wavelet transform, multitaper spectral analysis, and S-transform were applied to summary statistic arrays, and the resulting images were fed into convolutional neural networks. The modeling framework achieved high accuracy and power in detecting selection and can be a valuable tool for studying adaptive processes from genomic data.
MOLECULAR BIOLOGY AND EVOLUTION
(2023)
Article
Environmental Studies
Feilan Wang, Wing-Keung Wong, Geovanny Genaro Reivan Ortiz, Ata Al Shraah, Fatma Mabrouk, Jianfeng Li, Zeyun Li
Summary: Sustainable exports value addition is crucial for providing additional destinations for products and foreign exchange earnings. Mismanagement of natural resources and the role of artificial intelligence have asymmetric impacts on sustainable export value addition. Positive shock in natural resource management and negative shock in artificial intelligence have influential and dominant effects on increasing sustainable export value, highlighting the importance of policymaking based on these factors.
Review
Green & Sustainable Science & Technology
Hafiz Suliman Munawar, Ahmed W. A. Hammad, S. Travis Waller, Muhammad Jamaluddin Thaheem, Asheem Shrestha
Summary: This paper reviews the latest advancements in flood management based on image processing, artificial intelligence, and integrated approaches, with a focus on the post-disaster period. A novel framework is proposed to optimize flood management operations.
Article
Radiology, Nuclear Medicine & Medical Imaging
Shengping Cai, Yang Chen, Shixuan Zhao, Dehuai He, Yongjie Li, Nian Xiong, Zhidan Li, Shaoping Hu
Summary: This study developed a dynamic 3D radiomics analysis method using artificial intelligence to automatically assess the disease stages of COVID-19 patients based on CT images. The method showed high accuracy and good diagnostic performance.
EUROPEAN RADIOLOGY
(2022)
Article
Operations Research & Management Science
Carlos Galera-Zarco, Goulielmos Floros
Summary: With increasing urbanisation and the rapid growth of modern cities, ensuring the safety and protection of living conditions for inhabitants is crucial. This study explores the potential of artificial intelligence in disaster management and built assets operations by developing a deep learning model that assesses the structural condition of assets during seismic events. The model accurately predicts the damage status of individual elements, leading to operational improvements and providing essential information for quicker decision making and strengthened operational resilience in critical events.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Environmental Studies
Nannan Li, Zhenjing Gu, Gadah Albasher, Nouf Alsultan, Ambreen Fatemah
Summary: In recent years, the world has paid a lot of attention to sustainable development and resource productivity due to the increase in climate change. At the same time, the use of artificial intelligence in financial management and the development of new blockchains or cryptocurrencies have significantly impacted economic operations. This study investigates the influence of financial management and blockchains on environmental sustainability and resource productivity using monthly time series data from the United States economy. The findings indicate that artificial intelligence-based financial management improves environmental sustainability and resource productivity, while blockchain technology has mixed effects by reducing metallic resources but also contributing to environmental unsustainability. These findings are crucial in guiding the achievement of Sustainable Development Goals.
Article
Geosciences, Multidisciplinary
Omer Ekmekcioglu, Kerim Koc
Summary: This research introduces a novel step-wise binary prediction framework for assessing the susceptibility of geo-hydrological hazards, specifically floods and landslides. The framework consists of two major steps: predicting hazard-prone locations and classifying floods and landslides separately. The study utilizes historically experienced hazard locations and hazard conditioning factors to provide accurate predictions. The results demonstrate a strong agreement between the predicted and observed hazard locations, highlighting the effectiveness of the proposed hybrid prediction framework.
Article
Computer Science, Artificial Intelligence
Hyejin Jang, Sunhye Kim, Byungun Yoon
Summary: As technology development continues to accelerate, novelty analysis is becoming increasingly important in R&D planning and patent application. However, existing language models do not consider the unique characteristics of technical elements in patent documents nor provide explanations for their decisions. Therefore, we developed an eXplainable AI (XAI) model that evaluates novelty, considers the claim structure of a patent, and provides explanations.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Editorial Material
Biochemistry & Molecular Biology
Eric Wu, Kevin Wu, Roxana Daneshjou, David Ouyang, Daniel E. Ho, James Zou
Summary: A comprehensive overview of medical AI devices approved by the US Food and Drug Administration sheds light on limitations of the evaluation process that may mask vulnerabilities of devices when deployed on patients.
Review
Geosciences, Multidisciplinary
Di Huang, Shuaian Wang, Zhiyuan Liu
Summary: The rise in global warming and destructive human activities have led to an increase in catastrophic events worldwide, posing significant threats to human life and social stability. The emergency management (EM) system is crucial in saving lives and minimizing property damage. Recent years have seen a surge in contributions to prediction techniques for disaster events, including statistical analysis, artificial intelligence, and simulation methods, prompting the need for a systematic analysis of current works.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Environmental Studies
Xuan Peng, Saeed Mousa, Muddassar Sarfraz, Nassani Abdelmohsen, Mohamed Haffar
Summary: In recent years, there has been a growing global focus on natural resource management due to the increasing impact of climate change. The heavy reliance on mineral resource management by both developed and developing economies is a significant aspect of this debate. Additionally, the advancements in artificial intelligence-based financial management have transformed the operations and management prospects of ecological resources. This study examines the relationship between AI-based financial management and mineral resource management in the economy of the United States of America from 1980 to 2020. The findings reveal an asymmetric relationship between AI-based financial management and mineral resource rent, suggesting the need for the USA to redesign its mineral resource strategy and establish AI-based financial systems for improving resource management and long-term growth.
Article
Geosciences, Multidisciplinary
Ling Tan, Xianhua Wu, Zeshui Xu, Lianshui Li
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2019)
Article
Green & Sustainable Science & Technology
Kun Zhou, Ling Tan, Lianshui Li, Xiaohui Gao
Summary: The study highlights the insufficient motivation and low efficiency faced by China's new energy product export growth, with significant heterogeneity in power models and efficiency levels among countries, and institutional distance playing a crucial role in affecting efficiency.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Environmental Sciences
Ling Tan, Kun Zhou, Hui Zheng, Lianshui Li
Summary: The research shows that there is a negative correlation and inverted U-shaped relationship between temperature changes and economic output. Research areas and temperature variables have significant impacts on economic consequence analysis, with poor countries suffering adverse effects in hot climates. Future prediction models should consider resilience factors to study mitigation effects.
Article
Green & Sustainable Science & Technology
Ling Tan, David M. Schultz
Summary: Utilizing social-media data, this study developed a framework for rapid damage classification and recovery monitoring for urban floods. Findings from a case study in Chongqing, China, revealed that regions with more physical damage tended to express more negative emotions, government employees tended to convey positive information to reduce public panic, and students were more likely to express negative emotions.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Public, Environmental & Occupational Health
Ling Tan, Xianhua Wu, Ji Guo, Ernesto D. R. Santibanez-Gonzalez
Summary: The article describes how to use a Computable General Equilibrium model to assess the potential impact of the COVID-19 epidemic on the Chinese economy and various sectors, and proposes corresponding measures and suggestions.
Article
Biodiversity Conservation
Ling Tan, Weizhi Yao, Fei Chen, Lianshui Li
TROPICAL CONSERVATION SCIENCE
(2020)
