Barriers to rural women’s participation in social insurance for farmers, villagers, and nomads: the case of Iran DOI Creative Commons
Hamed Ghadermarzi

Frontiers in Sociology, Journal Year: 2024, Volume and Issue: 9

Published: Nov. 1, 2024

Since the enactment of Law Comprehensive Structure for Social Welfare and Security in Iran, only a small fraction its target has been accomplished significant part rural women have not covered by social insurance service yet. A few studies conducted on people. However, no study ever addressed issue with focus theoretical aspects sociology science, which is contribution present research. Therefore, research aimed to explore barriers women's participation insurance.

Language: Английский

Deep study on autonomous learning techniques for complex pattern recognition in interconnected information systems DOI
Zahra Mohtasham‐Amiri, Arash Heidari,

Nima Jafari

et al.

Computer Science Review, Journal Year: 2024, Volume and Issue: 54, P. 100666 - 100666

Published: Sept. 20, 2024

Language: Английский

Citations

9

Impact of Artificial Intelligence in Nursing for Geriatric Clinical Care for Chronic Diseases: A Systematic Literature Review DOI Creative Commons
Mahdieh Poodineh Moghadam,

Zabih Allah Moghadam,

Mohammad Reza Chalak Qazani

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 122557 - 122587

Published: Jan. 1, 2024

Language: Английский

Citations

3

Multi-channel advertising budget allocation: A novel method using Q-learning and mutual learning-based artificial bee colony DOI

B. Wang,

Pourya Zareeihemat

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 126649 - 126649

Published: Jan. 1, 2025

Language: Английский

Citations

0

A novel 3-step technique for 3D tumor reconstruction using generative adversarial networks and an attention-based long short-term memory DOI
Tangsen Huang, Xiangdong Yin,

Ensong Jiang

et al.

Research on Biomedical Engineering, Journal Year: 2025, Volume and Issue: 41(2)

Published: March 27, 2025

Language: Английский

Citations

0

A Transductive Learning-Based Early Warning System for Housing and Stock Markets With Off-Policy Optimization DOI Creative Commons
M.J. Ramezankhani, Albert Boghosian

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 141762 - 141784

Published: Jan. 1, 2024

Language: Английский

Citations

2

Melanoma detection: integrating dilated convolutional methods with mutual learning-based artificial bee colony and reinforcement learning DOI
Fengyu Hu, Jiayuan Zhang

Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 8(1)

Published: Nov. 8, 2024

Language: Английский

Citations

2

Wastewater treatment monitoring: Fault detection in sensors using transductive learning and improved reinforcement learning DOI
Jing Yang,

Ke Tian,

Huayu Zhao

et al.

Expert Systems with Applications, Journal Year: 2024, Volume and Issue: unknown, P. 125805 - 125805

Published: Nov. 1, 2024

Language: Английский

Citations

2

Enhancing Earth data analysis in 5G satellite networks: A novel lightweight approach integrating improved deep learning DOI Creative Commons
Yukun Yang, Kun Ren,

Jiong Song

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(11), P. e32071 - e32071

Published: May 30, 2024

Efficiently handling huge data amounts and enabling processing-intensive applications to run in faraway areas simultaneously is the ultimate objective of 5G networks. Currently, order distribute computing tasks, ongoing studies are exploring incorporation fog-cloud servers onto satellites, presenting a promising solution enhance connectivity remote areas. Nevertheless, analyzing copious produced by scattered sensors remains challenging endeavor. The conventional strategy transmitting this central server for analysis can be costly. In contrast centralized learning methods, distributed machine (ML) provides an alternative approach, albeit with notable drawbacks. This paper addresses comparative expenses systems tackle these challenges directly. It proposes creation integrated system that harmoniously merges cloud satellite network structures, leveraging strengths each system. integration could represent major breakthrough satellite-based networking technology streamlining processing from nodes cutting down on expenses. core approach lies adaptive tailoring techniques individual entities based their specific contextual nuances. experimental findings underscore prowess innovative lightweight strategy, LMAED2L (Enhanced Deep Learning Earth Data Analysis), across spectrum assignments, showcasing remarkable consistent performance under diverse operational conditions. Through strategic fusion frameworks, method emerges as dynamic effective remedy intricate encountered within networks interfaced servers. empirical reveal significant boost our novel over traditional average increase reward (4.1%), task completion rate (3.9%), delivered packets (3.4%). report suggests advancements will catalyze cutting-edge algorithms future networks, elevating responsiveness, efficiency, resource utilization new heights.

Language: Английский

Citations

1

Using an Artificial Neural Network for Vibration Analysis of Multi-Layered Composite Beams Located on the Elastic Foundation DOI
Yaqi Yang, Zhihui Jia

Journal of The Institution of Engineers (India) Series C, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 20, 2024

Language: Английский

Citations

0

A New Feature‐Based Biometric Identification System in IoT‐Powered Smart Cities Using a Hybrid Optimization Algorithm DOI Open Access
Mehdi Darbandi, Ali A. Ehsani, Farzad Bahrami

et al.

Security and Privacy, Journal Year: 2024, Volume and Issue: 8(1)

Published: Dec. 25, 2024

ABSTRACT The pervasive expansion of the Internet Things (IoT) year after has facilitated widespread sensing capabilities across various domains. Consequently, heightened concerns have arisen regarding authentication and security measures. There is a growing focus on biometrics in realm human identification applications, particularly context advancing biometric‐enhanced IoT applications. This trend garnering increasing attention as it unfolds. As new technologies developed, biometric‐based been seen an effective way to automatically identify people because its uniqueness impossibility fabricating it. Biometric identity systems make secure access management possible. However, due their almost identical physical traits, one biggest problems with conventional being able tell between twins. fact frequently results high false acceptance rates, putting system's at risk. Thus, solution addressed this work by applying multi‐biometric method based unique feature levels. Moreover, accuracy robustness biometric identifications are further enhanced both Real Coded Genetic Algorithm (RCGA) Fish Swarm (FSA). RCGA employed global search explore promising space guide toward optimal region. algorithm exploits capability AFSA, serving local final solution. Besides, proposed enhances discriminative power, enabling more precise trustworthy. Therefore, greatly contributes advancement increase fields.

Language: Английский

Citations

0