International Journal of Disaster Risk Reduction, Год журнала: 2024, Номер 112, С. 104782 - 104782
Опубликована: Авг. 24, 2024
Язык: Английский
World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 21(2), С. 1900 - 1908
Опубликована: Фев. 28, 2024
This review provides a succinct overview of the research conducted to evaluate effectiveness environmental legislation in enhancing disaster resilience, drawing insights from case studies Nigeria and United States. Environmental plays pivotal role mitigating impacts natural disasters, yet its fostering resilience remains subject debate. study employs comparative analysis approach, examining legislative frameworks their implementation two diverse contexts: Nigeria, representing developing nation with significant challenges, USA, developed robust regulatory mechanisms. Through comprehensive data collection analysis, this scrutinizes extent which contributes both countries. Key factors such as compliance, enforcement mechanisms, stakeholder engagement, institutional capacity are evaluated gauge efficacy frameworks. Findings reveal disparities between USA. In despite existence relevant laws, challenges persist due weaknesses, corruption, inadequate resources. Consequently, communities remain vulnerable recurrent exacerbating socio-economic degradation. Conversely, USA demonstrates more structured approach legislation, efficient enforcement, proactive risk management strategies. has led greater adaptive capacity, evidenced by effective preparedness, response, recovery measures. However, these disparities, identifies common areas for improvement contexts. Strengthening public awareness participation, promoting sustainable practices, international cooperation emerge crucial strategies bolster through legislation. underscores significance evaluating providing valuable policymakers, practitioners, stakeholders beyond. By addressing identified leveraging best nations can foster resilient future face escalating risks uncertainties.
Язык: Английский
Процитировано
21
International Journal of Hydrogen Energy, Год журнала: 2024, Номер 75, С. 567 - 577
Опубликована: Апрель 4, 2024
Язык: Английский
Процитировано
12
Environmental Research, Год журнала: 2024, Номер 249, С. 118246 - 118246
Опубликована: Янв. 24, 2024
Язык: Английский
Процитировано
9
Natural Hazards, Год журнала: 2025, Номер unknown
Опубликована: Янв. 3, 2025
Язык: Английский
Процитировано
1
Remote Sensing, Год журнала: 2024, Номер 16(12), С. 2159 - 2159
Опубликована: Июнь 14, 2024
An earthquake early-warning system (EEWS) is an indispensable tool for mitigating loss of life caused by earthquakes. The ability to rapidly assess the severity crucial effectively managing disasters and implementing successful risk-reduction strategies. In this regard, utilization Internet Things (IoT) network enables real-time transmission on-site intensity measurements. This paper introduces a novel approach based on machine-learning (ML) techniques accurately promptly determine analyzing seismic activity 2 s after onset p-wave. proposed model, referred as 2S1C1S, leverages data from single station component evaluate intensity. dataset employed in study, named “INSTANCE,” comprises Italian National Seismic Network (INSN) via hundreds stations. model has been trained substantial 50,000 instances, which corresponds 150,000 windows each, encompassing 3C. By capturing key features waveform traces, provides reliable estimation intensity, achieving impressive accuracy rate 99.05% forecasting any 2S1C1S can be seamlessly integrated into centralized IoT system, enabling swift alerts relevant authorities prompt response action. Additionally, comprehensive comparison conducted between results obtained method those derived conventional manual solution method, considered benchmark. experimental demonstrate that employing extreme gradient boosting (XGB), surpasses several ML benchmarks determining thus highlighting effectiveness methodology systems (EEWSs).
Язык: Английский
Процитировано
7
Progress in Disaster Science, Год журнала: 2024, Номер 23, С. 100347 - 100347
Опубликована: Июль 3, 2024
Seismology is among the ancient sciences that concentrate on earthquake disaster management (EQDM), which directly impact human life and infrastructure resilience. Such a pivot has made use of contemporary technologies. Nevertheless, there need for more reliable insightful solutions to tackle daily challenges intricacies natural stakeholders must confront. To consolidate substantial endeavors in this field, we undertake comprehensive survey interconnected More particularly, analyze data communication networks (DCNs) Internet Things (IoT), are main infrastructures seismic networks. In accordance, present conventional innovative signal-processing techniques seismology. Then, shed light evolution EQ sensors including acoustic based optical fibers. Furthermore, address role remote sensing (RS), robots, drones EQDM. Afterward, highlight social media contribution. Subsequently, elucidation diverse optimization employed seismology prolonging presented. Besides, paper analyzes important functions artificial intelligence (AI) can fulfill several areas Lastly, guide how prevent disasters preserve lives.
Язык: Английский
Процитировано
6
Earth Science Informatics, Год журнала: 2023, Номер 17(2), С. 869 - 891
Опубликована: Дек. 28, 2023
Язык: Английский
Процитировано
15
Natural Hazards, Год журнала: 2024, Номер unknown
Опубликована: Июнь 7, 2024
Abstract
The
Red
Sea
region,
situated
between
the
Arabian
and
African
Plates,
experiences
significant
seismic
activity
due
to
its
tectonic
dynamics,
with
earthquakes
ranging
from
minor
potentially
destructive
events.
This
study
aims
develop
smoothed
seismicity
models
for
region
by
using
an
enhanced
catalog
specific
Sea.
facilitates
a
detailed
spatial
temporal
analysis
of
events,
focusing
on
source
characterization
essential
probabilistic
hazard
assessments.
A
rigorous
declustering
method
excludes
foreshocks
aftershocks,
independent
uses
grid
(0.1
$$^{\circ
}$$
Язык: Английский
Процитировано
5
Journal of Global Information Management, Год журнала: 2025, Номер 33(1), С. 1 - 26
Опубликована: Янв. 24, 2025
Retransmitted messages online can have profound effects on disaster response; however, existing literature provides an incomplete account of why are retransmitted social media in disasters. In particular, there is a need to theorize the capabilities communication tools used for sending messages, because nowadays people send via different tools. This paper aims and explain how affect message retransmission by affecting generation characteristics. To test our account, we collected coded Twitter data from three disasters, employed five logistic regressions hypotheses. Our results confirm expectations that compared sent desktops, mobile devices less likely be helpful verifiable, but more visual attachments expressions anxiety.
Язык: Английский
Процитировано
0
Disaster Medicine and Public Health Preparedness, Год журнала: 2025, Номер 19
Опубликована: Янв. 1, 2025
Abstract Objective This study explores how we can improve the government’s research and technology for disasters safety. Methods employs Structural Equation Model (SEM) based on 268 experts’ perspectives. Results R&D performance exerts a directly significant impact achievement with coefficient of 0.429. Second, while professionality environment do not show direct effect achievement, they exhibit an indirect it 1.124 0.354, respectively. Third, (0.964), has positive (0.827). Conclusion Governments policymakers should develop disaster safety policies by understanding effects relationship factors related to improving achievement.
Язык: Английский
Процитировано
0