Advancing Social Equity in Urban UAV Logistics: Insights from the Academic Literature and Social Media DOI Creative Commons
Dong Zhang, Perry Pei‐Ju Yang, Jin Yeu Tsou

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 688 - 688

Published: Nov. 19, 2024

In recent years, the rapid growth of e-commerce and on-demand delivery services has placed a significant strain on urban logistics systems. Technological advances such as unmanned aerial vehicle (UAV)-based systems have thus emerged promising solutions in environments are increasingly being piloted worldwide. However, implementation UAV risks exacerbating social inequities, particularly marginalized communities that may disproportionately bear noise safety risks. To mitigate these risks, it is crucial to integrate equity considerations into logistics. This study explores factors through systematic literature review media analysis Xiaohongshu (the Little Red Book), popular Chinese platform known for its extensive user base active discussions issues. involves full-text examination, while latent Dirichlet allocation (LDA) topic modeling used analyze comment datasets. Each method identifies separately assesses their relative importance, resulting final identification 24 key provide holistic view public sentiment academic discourse. The findings reveal divide between concerns around systemic focus immediate needs. By synthesizing insights, this provides landscape actionable references policymakers stakeholders.

Language: Английский

Context-Aware Prediction with Secure and Lightweight Cognitive Decision Model in Smart Cities DOI Creative Commons
Fatima Al‐Quayed, Mamoona Humayun,

Thanaa S. Alnusairi

et al.

Cognitive Computation, Journal Year: 2025, Volume and Issue: 17(1)

Published: Jan. 15, 2025

Language: Английский

Citations

0
Multi-attribute-based self-stabilizing algorithm for leader election in distributed systems DOI
Amit Biswas, Manisha Singh, Gaurav Baranwal

et al.

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(4)

Published: Feb. 27, 2025

Language: Английский

Citations

0
Revolutionizing the energy sector: exploring diversified blockchain platforms for a sustainable future DOI Creative Commons
Athira Jayavarma,

Preetha Parakkat Kesava Panikker,

Manjula G. Nair

et al.

Frontiers in Blockchain, Journal Year: 2025, Volume and Issue: 8

Published: March 13, 2025

Blockchain technology has caused a significant transformation in the global energy sector as it is increasingly applied producing, distributing, trading, and managing energy. The incorporation of blockchain industry presents unprecedented opportunities for creating secure decentralized systems trading that are not only resilient but also transparent. paper explores detailed analysis various platforms endeavors to collapse existing gaps advanced research supporting development applications. Precisely, this gives in-depth details some popular platforms, primarily focuses on platforms’ security, scalability solutions, consensus methods, strategies mitigating cyberattacks, privacy-preserving mechanisms, regulatory considerations, integration artificial intelligence platform optimization suitability based information. It helps providers select best their projects. examination aims further improve efficiency, reliability, sustainability via most suitable platform.

Language: Английский

Citations

0
A survey and future outlook on indoor location fingerprinting privacy preservation DOI
Amir Fathalizadeh, Vahideh Moghtadaiee,

Mina Alishahi

et al.

Computer Networks, Journal Year: 2025, Volume and Issue: unknown, P. 111199 - 111199

Published: March 1, 2025

Language: Английский

Citations

0
Enhancing cyber defense strategies with discrete multi-dimensional Z-numbers: a multi-attribute decision-making approach DOI Creative Commons

Aiting Yao,

Chen Huang, Weiqi Zhang

et al.

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(5)

Published: March 19, 2025

Language: Английский

Citations

0
Group verifiable secure aggregate federated learning based on secret sharing DOI Creative Commons
Sufang Zhou, Lin Wang, Liqun Chen

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 21, 2025

Federated learning is a distributed machine approach designed to tackle the problems of data silos and security raw data. Nevertheless, it remains susceptible privacy leakage risks aggregation server tampering attacks. Current privacy-preserving methods often involve significant computational communication overheads, which can be challenging in resource-limited settings, hindering their practical application. To overcome these obstacles, this article proposes an efficient secure scheme based on secret sharing-GVSA. GVSA safeguards local models through masking technique improves system's resilience user dropouts by utilizing sharing. Furthermore, implements dual incorporates lightweight validation tags verify accuracy results. By adopting grouping strategy, effectively minimizes burden both users server, making well-suited for resource-constrained environments. We compare with leading existing assess its performance various experimental setups. Experimental results demonstrate that maintains high while preserving model accuracy. Compared FedAvg, incurs only approximately 7% additional overhead. compared other schemes same level, achieves 2.3 $$\times$$ improvement training speed.

Language: Английский

Citations

0
A hierarchical blockchain architecture for federated learning in edge computing networks DOI
Shuyang Ren, Choonhwa Lee

The Journal of Supercomputing, Journal Year: 2025, Volume and Issue: 81(7)

Published: May 2, 2025

Language: Английский

Citations

0
A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response DOI Creative Commons

Ripal Ranpara,

Shobhit K. Patel,

Om Prakash Kumar

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: May 14, 2025

Language: Английский

Citations

0
Enhancing Cyber Defense Strategies with Discrete Multidimensional Z-Numbers: A Multi-Attribute Decision-Making Approach DOI Open Access

Aiting Yao,

Chengzu Dong,

Weiqi Zhang

et al.

Published: July 3, 2024

With the rapid development of intelligent logistics and network environment, it has become an urgent problem to efficiently accurately handle analyse huge amount uncertain decision information. Traditional making methods often fail make best use complex incomplete information, especially in field cyber defence. To address these problems, this paper introduces a new mathematical tool, discrete multidimensional Z-numbers (MZs), for expressing dealing with uncertainty reliability defence decisions. In paper, we first introduce synthesis method Z-numbers, which allows us consider multi-source information strategy. Then, hidden probability MZs is calculated by using model, Z+−number proposed, improves expressiveness model uncertainty. Based on MZs, define variety utility functions build multi-attribute group framework around functions. The provides novel perspective analysing designing response strategies, against highly adaptive covert attacks. verified case security assessment company. results show that can significantly improve accuracy efficiency making, demonstrating its unique advantages wide application potential This integrated Z-number not only suitable but also efficient support tool defence, helps intelligence adaptability

Language: Английский

Citations

1
Advancing Social Equity in Urban UAV Logistics: Insights from the Academic Literature and Social Media DOI Creative Commons
Dong Zhang, Perry Pei‐Ju Yang, Jin Yeu Tsou

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 688 - 688

Published: Nov. 19, 2024

In recent years, the rapid growth of e-commerce and on-demand delivery services has placed a significant strain on urban logistics systems. Technological advances such as unmanned aerial vehicle (UAV)-based systems have thus emerged promising solutions in environments are increasingly being piloted worldwide. However, implementation UAV risks exacerbating social inequities, particularly marginalized communities that may disproportionately bear noise safety risks. To mitigate these risks, it is crucial to integrate equity considerations into logistics. This study explores factors through systematic literature review media analysis Xiaohongshu (the Little Red Book), popular Chinese platform known for its extensive user base active discussions issues. involves full-text examination, while latent Dirichlet allocation (LDA) topic modeling used analyze comment datasets. Each method identifies separately assesses their relative importance, resulting final identification 24 key provide holistic view public sentiment academic discourse. The findings reveal divide between concerns around systemic focus immediate needs. By synthesizing insights, this provides landscape actionable references policymakers stakeholders.

Language: Английский

Citations

1