Fuat Turk^1,*, Murat Luy², Necaattin Barışçı³, Fikret Yalçınkaya⁴

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 349-363, 2022, DOI:10.32604/iasc.2022.023710

Abstract Cases of kidney cancer have shown a rapid increase in recent years. Advanced technology has allowed bettering the existing treatment methods. Research on the subject is still continuing. Medical segmentation is also of increasing importance. In particular, deep learning-based studies are of great importance for accurate segmentation. Tumor detection is a relatively difficult procedure for soft tissue organs such as kidneys and the prostate. Kidney tumors, specifically, are a type of cancer with a higher incidence in older people. As age progresses, the importance of having diagnostic tests increases. In some cases, patients with kidney tumors may not show any… More >

Thirumoorthy Palanisamy^1,*, Daniyal Alghazzawi², Surbhi Bhatia³, Areej Abbas Malibari², Pankaj Dadheech⁴, Sudhakar Sengan⁵

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 227-244, 2022, DOI:10.32604/iasc.2022.023692

Abstract Wireless Sensor Networks (WSNs) are spatially distributed to independent sensor networks that can sense physical characteristics such as temperature, sound, pressure, energy, and so on. WSNs have secure link to physical environment and robustness. Data Aggregation (DA) plays a key role in WSN, and it helps to minimize the Energy Consumption (EC). In order to have trustworthy DA with a rate of high aggregation for WSNs, the existing research works have focused on Data Routing for In-Network Aggregation (DRINA). Yet, there is no accomplishment of an effective balance between overhead and routing. But EC required during DA remained unsolved. The… More >

S. Beatrice^*, Janaki Meena

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 331-347, 2022, DOI:10.32604/iasc.2022.023666

Abstract Discovering the information about several disorders prevailing in brain and neurology is by no means a new scientific technique. A neurological disorder of any human being can be analyzed using EEG (Electroencephalography) signal from the electrode’s output. Epilepsy (spontaneous recurrent seizure) detection is usually carried out by the physicians using a visual scanning of the signals produced by EEG, which is onerous and may be inaccurate. EEG signal is often used to determine epilepsy, for its merits, such as non-invasive, portable, and economical, can exhibit superior temporal tenacity. This paper surveys the existing artifact removal methods. It puts a new-fangled… More >

G. Chamundeeswari¹, S. Srinivasan^1,*, S. Prasanna Bharathi^1,2

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 515-534, 2022, DOI:10.32604/iasc.2022.023449

Abstract Remote sensing (RS) is a very reliable and effective way to monitor the environment and landscape changes. In today’s world topographic maps are very important in science, research, planning and management. It is quite possible to detect the changes based on RS data which is obtained at two different times. In this paper, we propose an optimal technique that handles problems like urban green space destruction and detection of crop stress assessment. Firstly, the optimal preprocessing is performed on the given RS dataset, for image enhancement using geometric correction and image registration. Secondly, we propose the improved cat swarm optimization… More >

Nadeem Fakhar Malik^1,*, Aamer Nadeem¹, Muddassar Azam Sindhu²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 429-455, 2022, DOI:10.32604/iasc.2022.023423

Abstract The testing of Ajax (Asynchronous JavaScript and XML) web applications poses novel challenges for testers because Ajax constructs dynamic web applications by using Asynchronous communication and run time Document Object Model (DOM) manipulation. Ajax involves extreme dynamism, which induces novel kind of issues like state explosion, triggering state changes and unreachable states etc. that require more demanding web-testing methods. Model based testing is amongst the effective approaches to detect faults in web applications. However, the state model generated for an Ajax application can be enormous and may be hit by state explosion problem for large number of user action based… More >

R. Rajasekar^1,*, P. Sivakumar²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 117-131, 2022, DOI:10.32604/iasc.2022.023372

Abstract The Internet of vehicles and vehicular ad-hoc networks (VANET) offers numerous opportunities for managing the transportation problems effectively. The high mobility and wireless communication in VANET lead to adequate network topology modifications, resulting in network instability and insecure data communication. With an unsteady flow of traffic, vehicles are unevenly distributed in the geographical areas in practice. A new type 2 fuzzy logic-based secure clustering (T2FLSC) with cloud-based data dissemination scheme called the T2FLSC-CDD model for the VANET has been introduced for resolving this issue. The vehicles are dynamically clustered by the use of the T2FLSC technique, which elects the CHs… More >

R. Punithavathi¹, R. Thanga Selvi², R. Latha³, G. Kadiravan^4,*, V. Srikanth⁵, Neeraj Kumar Shukla⁶

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 143-156, 2022, DOI:10.32604/iasc.2022.023344

Abstract Wireless sensor networks comprise a set of autonomous sensor nodes, commonly used for data gathering and tracking applications. Node localization and intrusion detection are considered as the major design issue in WSN. Therefore, this paper presents a new multi-objective manta ray foraging optimization (MRFO) based node localization with intrusion detection (MOMRFO-NLID) technique for WSN. The goal of the MOMRFO-NLID technique is to optimally localize the unknown nodes and determine the existence of intrusions in the network. The MOMRFO-NLID technique encompasses two major stages namely MRFO based localization of nodes and optimal Siamese Neural Network (OSNN) based intrusion detection. The OSNN… More >

Inamul Hasan^1,2,*, R. Mukesh², P. Radha Krishnan^1,2, R. Srinath¹, R. B. Dhanya Prakash²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 567-584, 2022, DOI:10.32604/iasc.2022.023252

Abstract In this research, the aerodynamic performance and flow characteristics of NASA SC (2)-0714 airfoil and HH02 airfoil in the helicopter main rotor are evidently analyzed. The supercritical airfoil is used in the aircraft for attaining better transonic and high-speed flow characteristics. Moreover, a specialized helicopter airfoil called HH02 is used in the Apache helicopter rotor for increasing the operational speed. As most of the high-speed helicopters are using four-bladed main rotor configuration, it is analyzed with prior attention. The lift and thrust act in different directions for the forward phase of the flight whereas the lift and thrust act in… More >

K. Saranya^1,*, K. Selva Bhuvaneswari²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 399-414, 2022, DOI:10.32604/iasc.2022.023149

Abstract This paper presents a novel fuzzy logic based Convolution Neural Network intelligent classifier for accurate image classification. The proposed approach employs a semantic class label model that classifies the input land cover images into a set of semantic categories and classes depending on the content. The intelligent feature selection algorithm selects the prominent attributes from the given data set using weighted attribute functions and uses fuzzy logic to build the rules based on the membership values. To annotate remote sensing images, the CNN method effectively creates semantics and categorises images. The decision manager then integrates the fuzzy logic rules with… More >

Venkateswari Pichaimani¹, K. R. Manjula^2,*

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 383-397, 2022, DOI:10.32604/iasc.2022.023105

Abstract The indoor positioning system comprises portable wireless devices that aid in finding the location of people or objects within the buildings. Identification of the items is through the capacity level of the signal received from various access points (i.e., Wi-Fi routers). The positioning of the devices utilizing some algorithms has drawn more attention from the researchers. Yet, the designed algorithm still has problems for accurate floor planning. So, the accuracy of position estimation with minimum error is made possible by introducing Gaussian Distributive Feature Embedding based Deep Recurrent Perceptive Neural Learning (GDFE-DRPNL), a novel framework. Novel features from the dataset… More >