Debasis Mohapatra¹, Sourav Kumar Bhoi¹, Kalyan Kumar Jena¹, Chittaranjan Mallick², Kshira Sagar Sahoo³, N. Z. Jhanjhi^4,*, Mehedi Masud⁵

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 51-64, 2022, DOI:10.32604/iasc.2022.024561

Abstract Most of the recent works on network science are focused on investigating various interactions among a set of entities present in a system that can be represented by multiplex network. Each type of relationship is treated as a layer of multiplex network. Some of the recent works on multiplex networks are focused on deriving layer similarity from node similarity where node similarity is evaluated using neighborhood similarity measures like cosine similarity and Jaccard similarity. But this type of analysis lacks in finding the set of nodes having the same influence in both the network. The discovery of influence similarity between… More >

G. R. Sreekanth¹, Adel Fahad Alrasheedi², K. Venkatachalam³, Mohamed Abouhawwash^4,5,*, S. S. Askar²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 249-265, 2022, DOI:10.32604/iasc.2022.024538

Abstract Brain tumor is considered as an unusual cell that presents and grows in the brain. Similarly, it may lead to cancerous or non-cancerous. So, to improve the survival rate of the patient and to give the best treatment at the earliest, it’s very necessary for early prediction of tumor. Accurate classification of tumor in the brain is important for improving the diagnosis. In accordance with that, various research programs are invited for the better treatment of the patients. Machine Learning (ML) algorithms are applied to help the health associates for the classification of brain tumor and present their diagnosis. This… More >

Honggeun Ji^1,2, Jina Kim³, Syjung Hwang⁴, Eunil Park^1,4,*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 593-607, 2022, DOI:10.32604/iasc.2022.024405

Abstract Cracks affect the robustness and adaptability of various infrastructures, including buildings, bridge piers, pavement, and pipelines. Therefore, the robustness and the reliability of automated crack detection are essential. In this study, we conducted image segmentation using various crack datasets by applying the advanced architecture of U-Net. First, we collected and integrated crack datasets from prior studies, including the cracks in buildings and pavements. For effective localization and detection of cracks, we used U-Net-based neural networks, ResU-Net, VGGU-Net, and EfficientU-Net. The models were evaluated by the five-fold cross-validation using several evaluation metrics including mean pixel accuracy (MPA), mean intersection over union… More >

Siti Nurul Aqmariah Mohd Kanafiah^1,*, Mohd Yusoff Mashor¹, Zeehaida Mohamed², Yap Chun Way¹, Shazmin Aniza Abdul Shukor¹, Yessi Jusman³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 687-697, 2022, DOI:10.32604/iasc.2022.024361

Abstract Malaria is categorised as a dangerous disease that can cause fatal in many countries. Therefore, early detection of malaria is essential to get rapid treatment. The malaria detection process is usually carried out with a 100x magnification of thin blood smear using microscope observation. However, the microbiologist required a long time to identify malaria types before applying any proper treatment to the patient. It also has difficulty to differentiate the species in trophozoite stages because of similar characteristics between species. To overcome these problems, a computer-aided diagnosis system is proposed to classify trophozoite stages of Plasmodium Knowlesi (PK), Plasmodium Falciparum… More >

K. Aruna^1,*, G. Pradeep²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 205-219, 2022, DOI:10.32604/iasc.2022.024317

Abstract Container technology is the latest lightweight virtualization technology which is an alternate solution for virtual machines. Docker is the most popular container technology for creating and managing Linux containers. Containers appear to be the most suitable medium for use in dynamic development, packaging, shipping and many other information technology environments. The portability of the software through the movement of containers is appreciated by businesses and IT professionals. In the docker container, one or more processes may run simultaneously. The main objective of this work is to propose a new algorithm called Ant Colony Optimization-based Light Weight Container (ACO-LWC) load balancing… More >

D. Kothandaraman^1,*, M. Manickam², A. Balasundaram³, D. Pradeep⁴, A. Arulmurugan⁵, Arun Kumar Sivaraman⁶, Sita Rani⁷, Barnali Dey⁸, R. Balakrishna⁹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 655-666, 2022, DOI:10.32604/iasc.2022.024134

Abstract This work implements a Decentralized Links Failure Prevention (DLFP) routing algorithm to promote enhanced and efficient Internet of Things (IoT). The work increases the mobility as well as an opportunity for loss of IoT node meeting links due to both mobility and blockers/interferers. The proposed algorithm overcomes loss issues as well as works in dynamically allocating alternate route from other IoT nodes available in near and selecting for efficient route in the network. When the link fails, bandwidth is reduced and coverage area problems for packets sending from source to destination is managed. The proposed algorithm works with light-weight wireless… More >

R. Anand Babu^1,*, S. Kannan²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 307-323, 2022, DOI:10.32604/iasc.2022.024098

Abstract An Intrusion detection system (IDS) is extensively used to identify cyber-attacks preferably in real-time and to achieve integrity, confidentiality, and availability of sensitive information. In this work, we develop a novel IDS using machine learning techniques to increase the performance of the attack detection process. In order to cope with high dimensional feature-rich traffic in large networks, we introduce a Bat-Inspired Optimization and Correlation-based Feature Selection (BIOCFS) algorithm and an ensemble classification approach. The BIOCFS is introduced to estimate the correlation of the identified features and to choose the ideal subset for training and testing phases. The Ensemble Classifier (EC)… More >

Mani Deepak Choudhry^1,*, B. Aruna Devi², M. Sundarrajan³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 267-278, 2022, DOI:10.32604/iasc.2022.024024

Abstract Internet of Remote things (IoRT) has gained recent attention and is considered as one most prominent research topics being carried out by numerous researchers worldwide. IoRT is being used in various applications and this paper mainly concentrates on the healthcare industry wherein it could be used effectively for patient monitoring. IoRT plays a crucial role in monitoring the patients in any healthcare center remotely by allowing simultaneous video transmissions possible from the emergency areas like Intensive Care Unit (ICU). Considering general scenarios, the video transmissions are done by the main use of Gaussian distribution. With the help of the proposed… More >

Jenson Jose^1,*, Jose P. Therattil²

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 339-355, 2022, DOI:10.32604/iasc.2022.023863

Abstract The Wireless Power Transmission (WPT) technology is a significant source of operation in the field of power transmission with tremendous potential in a wide range of applications. This paper proposes a novel strategy for L2CL-LCL topology, which comprises two capacitors and one inductor in the essential and one capacitor and one inductor in the auxiliary. Using MATLAB simulation, this paper compares the traditional DSLCL system and the proposed L2CL-LCL. The various parameters of this system are simulated. In the current system, input and output power are set to 200.1 and 182.4 W. The common framework’s start to finish efficiency can… More >

Mahdi Souzanchi-K¹, Mohammad-R Akbarzadeh-T^1,*, Nadia Naghavi¹, Ali Sharifnezhad², Vahab Khoshdel³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 279-294, 2022, DOI:10.32604/iasc.2022.023717

Abstract Sliding mode control is often used for systems with parametric uncertainties due to its desirable robustness and stability, but this approach carries undesirable chattering. Similarly, joint elasticity is a common phenomenon induced by transmission systems in robots, but it presents additional complexity in robot dynamics that could lead to robot vibrations or even instability. Coupling these two phenomena presents further compounded challenges, particularly when faced with the human interface's added uncertainties. Here, a stable voltage-based adaptive fuzzy strategy to sliding mode control is proposed for an elastic joint robot arm that uses a human's upper limb electromyogram (EMG) signals to… More >