S. J. K. Jagadeesh Kumar¹, P. Parthasarathi², Mofreh A. Hogo³, Mehedi Masud⁴, Jehad F. Al-Amri⁵, Mohamed Abouhawwash^6,7,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2363-2378, 2023, DOI:10.32604/iasc.2023.033800

Abstract Women from middle age to old age are mostly screened positive for Breast cancer which leads to death. Times over the past decades, the overall survival rate in breast cancer has improved due to advancements in early-stage diagnosis and tailored therapy. Today all hospital brings high awareness and early detection technologies for breast cancer. This increases the survival rate of women. Though traditional breast cancer treatment takes so long, early cancer techniques require an automation system. This research provides a new methodology for classifying breast cancer using ultrasound pictures that use deep learning and the combination of the best characteristics.… More >

M. P. Thiruvenkatasuresh^1,*, Surbhi Bhatia², Shakila Basheer³, Pankaj Dadheech⁴

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1767-1782, 2023, DOI:10.32604/iasc.2023.033711

Abstract The study aimed to apply to Machine Learning (ML) researchers working in image processing and biomedical analysis who play an extensive role in comprehending and performing on complex medical data, eventually improving patient care. Developing a novel ML algorithm specific to Diabetic Retinopathy (DR) is a challenge and need of the hour. Biomedical images include several challenges, including relevant feature selection, class variations, and robust classification. Although the current research in DR has yielded favourable results, several research issues need to be explored. There is a requirement to look at novel pre-processing methods to discard irrelevant features, balance the obtained… More >

Abdulelah Alwabel^*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2217-2232, 2023, DOI:10.32604/iasc.2023.033703

Abstract The reliability and availability of cloud systems have become major concerns of service providers, brokers, and end-users. Therefore, studying fault-tolerance mechanisms in cloud computing attracts intense attention in industry and academia. The task-scheduling mechanisms can improve the fault-tolerance level of cloud systems. A task-scheduling mechanism distributes tasks to a group of instances to be executed. Much work has been undertaken in this direction to improve the overall outcome of cloud computing, such as improving service quality and reducing power consumption. However, little work on task scheduling has studied the problem of lost tasks from the broker’s perspective. Task loss can… More >

R. Shanthakumari¹, Yun-Cheol Nam², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1991-2005, 2023, DOI:10.32604/iasc.2023.033696

Abstract Smart cities make use of a variety of smart technology to improve societies in better ways. Such intelligent technologies, on the other hand, pose significant concerns in terms of power usage and emission of carbons. The suggested study is focused on technological networks for big data-driven systems. With the support of software-defined technologies, a transportation-aided multicast routing system is suggested. By using public transportation as another communication platform in a smart city, network communication is enhanced. The primary objective is to use as little energy as possible while delivering as much data as possible. The Attribute Decision Making with Capacitated… More >

Ghassan Mousa¹, Ayman A. Aly², Imran Khan³, Dag Øivind Madsen^4,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1963-1978, 2023, DOI:10.32604/iasc.2023.033627

Abstract The economics, infrastructure, transportation, and level of living of a country are all influenced by energy. The gap between energy usage and availability is a global issue. Currently, all countries rely on fossil fuels for energy generation, and these fossil fuels are not sustainable. The hydrogen proton exchange membrane fuel cell (PEMFC) power system is both clean and efficient. The fuel delivery system and the PEMFC make up the majority of the PEMFC power system. The lack of an efficient, safe, and cost-effective hydrogen storage system is still a major barrier to its widespread use. Solid hydrogen storage has the… More >

Mrim M. Alnfiai^*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1653-1669, 2023, DOI:10.32604/iasc.2023.033577

Abstract Sign language is mainly utilized in communication with people who have hearing disabilities. Sign language is used to communicate with people having developmental impairments who have some or no interaction skills. The interaction via Sign language becomes a fruitful means of communication for hearing and speech impaired persons. A Hand gesture recognition system finds helpful for deaf and dumb people by making use of human computer interface (HCI) and convolutional neural networks (CNN) for identifying the static indications of Indian Sign Language (ISL). This study introduces a shark smell optimization with deep learning based automated sign language recognition (SSODL-ASLR) model… More >

Sakorn Mekruksavanich¹, Anuchit Jitpattanakul^2,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2111-2128, 2023, DOI:10.32604/iasc.2023.033542

Abstract The automated evaluation and analysis of employee behavior in an Industry 4.0-compliant manufacturing firm are vital for the rapid and accurate diagnosis of work performance, particularly during the training of a new worker. Various techniques for identifying and detecting worker performance in industrial applications are based on computer vision techniques. Despite widespread computer vision-based approaches, it is challenging to develop technologies that assist the automated monitoring of worker actions at external working sites where camera deployment is problematic. Through the use of wearable inertial sensors, we propose a deep learning method for automatically recognizing the activities of construction workers. The… More >

Aravind Athimoolam^1,*, Karthik Balasubramanian²

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1331-1347, 2023, DOI:10.32604/iasc.2023.033465

Abstract This paper focuses on the development of a diagnostic tool for detecting insulated gate bipolar transistor power electronic switch flaws caused by both open and short circuit faults in multi-level inverter time-frequency output voltage specifications. High-resolution laboratory virtual instrument engineering workbench software testing tool with a sample rate data collection system, as well as specialized signal processing and soft computing technologies, are used in this proposed method. On a single-phase cascaded H-bridge multilevel inverter, simulation and experimental investigations of both open and short issues of the insulated gate bipolar transistor components are performed out. In all conceivable switch issues, the… More >

Reem Alkanhel¹, Kalaiselvi Chinnathambi², C. Thilagavathi³, Mohamed Abouhawwash^4,5, Mona A. Al duailij⁶, Manal Abdullah Alohali⁷, Doaa Sami Khafaga^6,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1571-1583, 2023, DOI:10.32604/iasc.2023.033430

Abstract Wireless Sensor Networks are a group of sensors with inadequate power sources that are installed in a particular region to gather information from the surroundings. Designing energy-efficient data gathering methods in large-scale Wireless Sensor Networks (WSN) is one of the most difficult areas of study. As every sensor node has a finite amount of energy. Battery power is the most significant source in the WSN. Clustering is a well-known technique for enhancing the power feature in WSN. In the proposed method multi-Swarm optimization based on a Genetic Algorithm and Adaptive Hierarchical clustering-based routing protocol are used for enhancing the network’s… More >

Tan Nguyen Van¹, Huy Q. Tran^2,*, Vinh Xuan Ha³, Cheolkeun Ha⁴, Phu Huynh Minh¹

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2441-2456, 2023, DOI:10.32604/iasc.2023.033368

Abstract Electro-hydraulic actuators (EHA) have recently played a significant role in modern industrial applications, especially in systems requiring extremely high precision. This can be explained by EHA’s ability to precisely control the position and force through advanced sensors and innovative control algorithms. One of the promising approaches to improve control accuracy for EHA systems is applying classical to modern control algorithms, in which the proportional–integral–derivative (PID) algorithm, fuzzy logic controller, and a hybrid of these methods are popular options. In this paper, we developed a novel version of the fuzzy control algorithm and linear feedback control method, namely fuzzy linear feedback… More >