Azza Abdullah Alnssayan, Mohammad Mahdi Hassan^*, Suliman A. Alsuhibany

Computer Systems Science and Engineering, Vol.40, No.3, pp. 927-945, 2022, DOI:10.32604/csse.2022.016734

Abstract The digitalization of healthcare-related information service systems has become a trend across the world. However, several crucial services are still provided manually due to a lack of trust in digital solutions. One such service is keeping records of children’s vaccination, which still relies on a paper-based file system in most parts of the world. This approach causes serious data integrity problems. Recently, healthcare has become a potential application area of the blockchain, as it can preserve and protect highly sensitive private medical records while sharing these records in a decentralized manner without losing personal ownership. Therefore, we propose a new… More >

Farzaneh Khorasani¹, Morteza Mohammadi Zanjireh^1,*, Mahdi Bahaghighat¹, Qin Xin²

Computer Systems Science and Engineering, Vol.40, No.3, pp. 1085-1098, 2022, DOI:10.32604/csse.2022.016003

Abstract With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected… More >

Hashem Alyami¹, Mohd Nadeem², Wael Alosaimi³, Abdullah Alharbi³, Rajeev Kumar^4,*, Bineet Kumar Gupta⁴, Alka Agrawal², Raees Ahmad Khan²

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 707-716, 2022, DOI:10.32604/iasc.2022.020780

Abstract Software or web application security is the main objective in the era of Information Technology (IT) and Artificial Intelligence (AI). Distinguishing proof of security at the initial stage produces significant results to comprehend the administration of security relics for best potential outcomes. A security alternative gives several methods and algorithms to ensure the software security. Security estimation is the vital factor in assessing, administrating, controlling security to improve the nature of security. It is to be realized that assessment of security at early stage of development helps in identifying distinctive worms, dangers, weaknesses and threats. This paper will talk about… More >

Wen-Tsai Sung¹, Sung-Jung Hsiao^2,*, Chung-Yen Hsiao¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1223-1240, 2022, DOI:10.32604/iasc.2022.020746

Abstract This research is based on the system architecture of Edge Computing in the AIoT (Artificial Intelligence & Internet of Things) field. In terms of receiving data, the authors proposed approach employed the camera module as the video source, the ultrasound module as the distance measurement source, and then compile C++ with Raspberry Pi 4B for image lane analysis, while Jetson Nano uses the YOLOv3 algorithm for image object detection. The analysis results of the two single-board computers are transmitted to Motoduino U1 in binary form via GPIO, which is used for data integration and load driving. The load drive has… More >

Iftikhar Ahmad^1,*, Abdulwahab Ali Almazroi², Mohammed A. Alqarni³, Muhammad Kashif Nawaz¹

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1131-1142, 2022, DOI:10.32604/iasc.2022.020715

Abstract In a classical k-min search problem, an online player wants to buy k units of an asset with the objective of minimizing the total buying cost. The problem setting allows the online player to view only a single price quotation at each time step. A price quotation is the price of one unit of an asset. After receiving the price quotation, the online player has to decide on the number of units to buy. The objective of the online player is to buy the required k units in a fixed length investment horizon. Online algorithms are proposed in the literature… More >

R. P. Narmadha^1,*, N. Sengottaiyan², R. J. Kavitha³

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1257-1271, 2022, DOI:10.32604/iasc.2022.020679

Abstract In agriculture, plant diseases are mainly accountable for reduction in productivity and leads to huge economic loss. Rice is the essential food crop in Asian countries and it gets easily affected by different kinds of diseases. Because of the advent of computer vision and deep learning (DL) techniques, the rice plant diseases can be detected and reduce the burden of the farmers to save the crops. To achieve this, a new DL based rice plant disease diagnosis is developed using Densely Convolution Neural Network (DenseNet) with multilayer perceptron (MLP), called DenseNet169-MLP. The proposed model aims to classify the rice plant… More >

Hanan A. Hosni Mahmoud, Amal H. Alharbi, Norah S. Alghamdi^*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1273-1286, 2022, DOI:10.32604/iasc.2022.020662

Abstract In this paper we propose a computerized breast cancer detection and breast masses classification system utilizing mammograms. The motivation of the proposed method is to detect breast cancer tumors in early stages with more accuracy and less negative false cases. Our proposed method utilizes clustering of different features by segmenting the breast mammogram and then extracts deep features using the presented Convolution Neural Network (CNN). The extracted features are then combined with subjective features such as shape, texture and density. The combined features are then utilized by the Extreme Learning Machine Clustering (ELMC) algorithm to combine segments together to identify… More >

Maryam Altalhi¹, Sami Ur Rehman², Fakhre Alam², Ala Abdulsalam Alarood³, Amin ur Rehman², M. Irfan Uddin^4,*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 961-969, 2022, DOI:10.32604/iasc.2022.020607

Abstract The proper computation of geometric parameters of the aorta and coronary arteries are very important for surgery planning, disease diagnoses, and age-related changes observation in the vessels. The accurate knowledge about the geometry of aorta and coronary arteries is required for the proper investigation of heart related diseases. The geometry of aorta and coronary arteries includes the diameter of the ascending and descending aorta and coronary arteries, length of the coronary arteries, branching angles of the coronary arteries and branching points. These geometric parameters from arteries can be computed from the 3D image data. In this paper, we propose an… More >

Andang Sunarto^1,*, Praveen Agarwal^2,3,4, Jumat Sulaiman⁵, Jackel Vui Lung Chew⁶

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1173-1184, 2022, DOI:10.32604/iasc.2022.020542

Abstract Solving time-fractional diffusion equation using a numerical method has become a research trend nowadays since analytical approaches are quite limited. There is increasing usage of the finite difference method, but the efficiency of the scheme still needs to be explored. A half-sweep finite difference scheme is well-known as a computational complexity reduction approach. Therefore, the present paper applied an unconditionally stable half-sweep finite difference scheme to solve the time-fractional diffusion equation in a one-dimensional model. Throughout this paper, a Caputo fractional operator is used to substitute the time-fractional derivative term approximately. Then, the stability of the difference scheme combining the… More >

Saiful Izzuan Hussain^*, Nadiah Ruza

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1143-1156, 2022, DOI:10.32604/iasc.2022.020508

Abstract Coronavirus (COVID-19) is a pandemic disease classified by the World Health Organization. This virus triggers several coughing problems (e.g., flu) that include symptoms of fever, cough, and pneumonia, in extreme cases. The human sputum or blood samples are used to detect this virus, and the result is normally available within a few hours or at most days. In this research, we suggest the implementation of automated deep learning without require handcrafted expertise of data scientist. The model developed aims to give radiologists a second-opinion interpretation and to minimize clinicians’ workload substantially and help them diagnose correctly. We employed automated deep… More >