Open Access

RETRACTION

Nan Pan^1,*, Dilin Pan², Yi Liu²
Intelligent Automation & Soft Computing, Vol.40, pp. 147-147, 2025, DOI:10.32604/iasc.2025.062708 - 29 January 2025
Abstract This article has no abstract. More >

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RETRACTION

Nan Pan^1,*, Yi Liu², Dilin Pan², Junbing Qian¹, Gang Li³
Intelligent Automation & Soft Computing, Vol.40, pp. 145-145, 2025, DOI:10.32604/iasc.2025.062707 - 29 January 2025
Abstract This article has no abstract. More >

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ARTICLE

Mustafa Youldash¹, Atta Rahman^2,*, Manar Alsayed¹, Abrar Sebiany¹, Joury Alzayat¹, Noor Aljishi¹, Ghaida Alshammari¹, Mona Alqahtani¹
Intelligent Automation & Soft Computing, Vol.40, pp. 125-143, 2025, DOI:10.32604/iasc.2025.058509 - 23 January 2025
Abstract Diabetic retinopathy (DR) is a complication of diabetes that can lead to reduced vision or even blindness if left untreated. Therefore, early and accurate detection of this disease is crucial for diabetic patients to prevent vision loss. This study aims to develop a deep-learning approach for the early and precise diagnosis of DR, as manual detection can be time-consuming, costly, and prone to human error. The classification task is divided into two groups for binary classification: patients with DR (diagnoses 1–4) and those without DR (diagnosis 0). For multi-class classification, the categories are no DR,… More >

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REVIEW

Ghulam E Mustafa Abro^1,*, Ayman M Abdallah^1,2, Faizan Zahid³, Saleem Ahmed⁴
Intelligent Automation & Soft Computing, Vol.40, pp. 99-123, 2025, DOI:10.32604/iasc.2025.060364 - 23 January 2025
Abstract This review synthesises and assesses the most recent developments in Unmanned Aerial Vehicles (UAVs) and swarm robotics, with a specific emphasis on optimisation strategies, path planning, and formation control. The study identifies key methodologies that are driving progress in the field by conducting a comprehensive analysis of seven critical publications. The following are included: sensor-based platforms that facilitate effective obstacle avoidance, cluster-based hierarchical path planning for efficient navigation, and adaptive hybrid controllers for dynamic environments. The review emphasises the substantial contribution of optimisation techniques, including Max-Min Ant Colony Optimisation (MMACO), to the improvement of convergence… More >

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ARTICLE

Ayoub Ghani^1,*, Ahmed Zinedine¹, Mohammed El Mohajir²
Intelligent Automation & Soft Computing, Vol.40, pp. 75-98, 2025, DOI:10.32604/iasc.2025.060143 - 23 January 2025
Abstract The Internet of Things (IoT) advances allow healthcare providers to distantly gather and immediately analyze patient health data for diagnostic purposes via connected health devices. In a COVID-19-like pandemic, connected devices can mitigate virus spread and make essential information, such as respiratory patterns, available to healthcare professionals. However, these devices generate vast amounts of data, rendering them susceptible to privacy breaches, and data leaks. Blockchain technology is a robust solution to address these issues in telemedicine systems. This paper proposes a blockchain-based access management solution to enhance patient privacy and secure telehealth and telemedicine data.… More >

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51

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ARTICLE

Haider H. Al-Mahmood^1,*, Saad N. Alsaad²
Intelligent Automation & Soft Computing, Vol.40, pp. 53-74, 2025, DOI:10.32604/iasc.2024.059691 - 10 January 2025
Abstract In secure communications, lightweight encryption has become crucial, particularly for resource-constrained applications such as embedded devices, wireless sensor networks, and the Internet of Things (IoT). As these systems proliferate, cryptographic approaches that provide robust security while minimizing computing overhead, energy consumption, and memory usage are becoming increasingly essential. This study examines lightweight encryption techniques utilizing chaotic maps to ensure secure data transmission. Two algorithms are proposed, both employing the Logistic map; the first approach utilizes two logistic chaotic maps, while the second algorithm employs a single logistic chaotic map. Algorithm 1, including a two-stage mechanism… More >

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ARTICLE

Mahmood Alsaadi, Mohammed E. Seno^*, Mohammed I. Khalaf
Intelligent Automation & Soft Computing, Vol.40, pp. 29-52, 2025, DOI:10.32604/iasc.2024.060390 - 10 January 2025
（This article belongs to the Special Issue: Machine Learning for Privacy and Security in Internet of Things (IoT))
Abstract The agility of Internet of Things (IoT) software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments. Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications. To handle the interfacing complexity problem, this article introduces a Semantic Interfacing Obscuration Model (SIOM) for IoT software-engineered platforms. The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model. Based on the level of obscuration between the infrastructure hardware to the end-user software, the modifications through device replacement, More >

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ARTICLE

Nada Mohammed Murad¹, Adnan Yousif Dawod², Saadaldeen Rashid Ahmed^3,4,*, Ravi Sekhar⁵, Pritesh Shah⁵
Intelligent Automation & Soft Computing, Vol.40, pp. 1-27, 2025, DOI:10.32604/iasc.2024.058624 - 10 January 2025
Abstract This study introduces an innovative hybrid approach that integrates deep learning with blockchain technology to improve cybersecurity, focusing on network intrusion detection systems (NIDS). The main goal is to overcome the shortcomings of conventional intrusion detection techniques by developing a more flexible and robust security architecture. We use seven unique machine learning models to improve detection skills, emphasizing data quality, traceability, and transparency, facilitated by a blockchain layer that safeguards against data modification and ensures auditability. Our technique employs the Synthetic Minority Oversampling Technique (SMOTE) to equilibrate the dataset, therefore mitigating prevalent class imbalance difficulties… More >

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