Le Quang Thao^1,2,*, Duong Duc Cuong², Vu Manh Hung³, Le Thanh Vinh³, Doan Trong Nghia⁴, Dinh Ha Hai³, Nguyen Nhan Nhi³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3517-3530, 2023, DOI:10.32604/iasc.2023.031026

Abstract The recent outbreak of the coronavirus disease of 2019 (Covid-19) has been causing many disruptions among the education systems worldwide, most of them due to the abrupt transition to online learning. The sudden upsurge in digital electronic devices usage, namely personal computers, laptops, tablets and smartphones is unprecedented, which leads to a new wave of both mental and physical health problems among students, for example eye-related illnesses. The overexposure to electronic devices, extended screen time usage and lack of outdoor sunlight have put a consequential strain on the student’s ophthalmic health because of their young age and a relative lack… More >

S. Ayshwarya Lakshmi^1,*, K. Anandavelu²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3403-3413, 2023, DOI:10.32604/iasc.2023.030970

Abstract Skin cancer segmentation is a critical task in a clinical decision support system for skin cancer detection. The suggested enhanced cuckoo search based optimization model will be used to evaluate several metrics in the skin cancer picture segmentation process. Because time and resources are always limited, the proposed enhanced cuckoo search optimization algorithm is one of the most effective strategies for dealing with global optimization difficulties. One of the most significant requirements is to design optimal solutions to optimize their use. There is no particular technique that can answer all optimization issues. The proposed enhanced cuckoo search optimization method indicates… More >

E. Gokulakannan^*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3415-3427, 2023, DOI:10.32604/iasc.2023.030965

Abstract Deep learning is the subset of artificial intelligence and it is used for effective decision making. Wireless Sensor based automated irrigation system is proposed to monitor and cultivate crop. Our system consists of Distributed wireless sensor environment to handle the moisture of the soil and temperature levels. It is automated process and useful for minimizing the usage of resources such as water level, quality of the soil, fertilizer values and controlling the whole system. The mobile app based smart control system is designed using deep belief network. This system has multiple sensors placed in agricultural field and collect the data.… More >

M. Vargheese^1,*, S. Vanithamani², D. Stalin David³, Ganga Rama Koteswara Rao⁴

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3479-3499, 2023, DOI:10.32604/iasc.2023.030948

Abstract Wireless networks with no infrastructure arise as a result of multiple wireless devices working together. The Mobile Ad hoc Network (MANET) is a system for connecting independently located Mobile Nodes (MNs) via wireless links. A MANET is self-configuring in telecommunications, while MN produces non-infrastructure networks that are entirely decentralized. Both the MAC and routing layers of MANETs take into account issues related to Quality of Service (QoS). When culling a line of optical discernment communication, MANET can be an effective and cost-saving route cull option. To maintain QoS, however, more or fewer challenges must be overcome. This paper proposes a… More >

Wenjia Xiang¹, Xiaoyu Li^1,*, Zirui He¹, Chenjing Su¹, Wangchi Cheng², Chao Lu³, Shan Yang⁴

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3627-3639, 2023, DOI:10.32604/iasc.2023.030904

Abstract Estimating the intention of space objects plays an important role in aircraft design, aviation safety, military and other fields, and is an important reference basis for air situation analysis and command decision-making. This paper studies an intention estimation method based on fuzzy theory, combining probability to calculate the intention between two objects. This method takes a space object as the origin of coordinates, observes the target’s distance, speed, relative heading angle, altitude difference, steering trend and etc., then introduces the specific calculation methods of these parameters. Through calculation, values are input into the fuzzy inference model, and finally the action… More >

Hanan Abdullah Mengash¹, Alaaeldin M. Hafez², Hanan A. Hosni Mahmoud^3,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3129-3140, 2023, DOI:10.32604/iasc.2023.030836

Abstract Encephalitis is a brain inflammation disease. Encephalitis can yield to seizures, motor disability, or some loss of vision or hearing. Sometimes, encephalitis can be a life-threatening and proper diagnosis in an early stage is very crucial. Therefore, in this paper, we are proposing a deep learning model for computerized detection of Encephalitis from the electroencephalogram data (EEG). Also, we propose a Density-Based Clustering model to classify the distinctive waves of Encephalitis. Customary clustering models usually employ a computed single centroid virtual point to define the cluster configuration, but this single point does not contain adequate information. To precisely extract accurate… More >

Amal H. Alharbi¹, S. Karthick², K. Venkatachalam³, Mohamed Abouhawwash^4,5, Doaa Sami Khafaga^1,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2773-2787, 2023, DOI:10.32604/iasc.2023.030763

Abstract Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security techniques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of… More >

S. Sadesh^1,*, Osamah Ibrahim Khalaf², Mohammad Shorfuzzaman³, Abdulmajeed Alsufyani³, K. Sangeetha⁴, Mueen Uddin⁵

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3365-3384, 2023, DOI:10.32604/iasc.2023.030751

Abstract Web usage mining, content mining, and structure mining comprise the web mining process. Web-Page Recommendation (WPR) development by incorporating Data Mining Techniques (DMT) did not include end-users with improved performance in the obtained filtering results. The cluster user profile-based clustering process is delayed when it has a low precision rate. Markov Chain Monte Carlo-Dynamic Clustering (MC²-DC) is based on the User Behavior Profile (UBP) model group’s similar user behavior on a dynamic update of UBP. The Reversible-Jump Concept (RJC) reviews the history with updated UBP and moves to appropriate clusters. Hamilton’s Filtering Framework (HFF) is designed to filter user data… More >

R. Radha^1,*, R. Gopalakrishnan²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3113-3127, 2023, DOI:10.32604/iasc.2023.030667

Abstract In the field of diagnosis of medical images the challenge lies in tracking and identifying the defective cells and the extent of the defective region within the complex structure of a brain cavity. Locating the defective cells precisely during the diagnosis phase helps to fight the greatest exterminator of mankind. Early detection of these defective cells requires an accurate computer-aided diagnostic system (CAD) that supports early treatment and promotes survival rates of patients. An earlier version of CAD systems relies greatly on the expertise of radiologist and it consumed more time to identify the defective region. The manuscript takes the… More >

Fadl Dahan^1,2,*, Abdulelah Alwabel³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3385-3402, 2023, DOI:10.32604/iasc.2023.030651

Abstract In recent years, cloud computing has provided a Software As A Service (SaaS) platform where the software can be reused and applied to fulfill complicated user demands according to specific Quality of Services (QoS) constraints. The user requirements are formulated as a workflow consisting of a set of tasks. However, many services may satisfy the functionality of each task; thus, searching for the composition of the optimal service while maximizing the QoS is formulated as an NP-hard problem. This work will introduce a hybrid Artificial Bee Colony (ABC) with a Cuckoo Search (CS) algorithm to untangle service composition problem. The… More >