Jing Peng^1,2,4, Chaoyang Xia², Yuanwei Xu³, Xiaojie Li², Xi Wu², Xiao Han^1,4, Xinlai Chen⁵, Yucheng Chen³, Zhe Cui^1,4,*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 259-272, 2021, DOI:10.32604/iasc.2021.016749

Abstract Cardiomyopathy is a group of diseases that affect the heart and can cause serious health problems. Segmentation and classification are important for automating the clinical diagnosis and treatment planning for cardiomyopathy. However, this automation is difficult because of the poor quality of cardiac magnetic resonance (CMR) imaging data and varying dimensions caused by movement of the ventricle. To address these problems, a deep multi-task framework based on a convolutional neural network (CNN) is proposed to segment the left ventricle (LV) myocardium and classify cardiopathy simultaneously. The proposed model consists of a longitudinal encoder–decoder structure that obtains high- and low-level features… More >

Adel Hamdan Mohammad^*

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 65-80, 2021, DOI:10.32604/iasc.2021.016140

Abstract Intrusion detection is an important topic that aims at protecting computer systems. Besides, feature selection is crucial for increasing the performance of intrusion detection. This paper employs a new hybrid feature selection model for intrusion detection. The implemented model uses Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) algorithms in a new manner. In addition, this study introduces two new models called (PSO-GWO-NB) and (PSO-GWO-ANN) for feature selection and intrusion detection. PSO and GWO show emergent results in feature selection for several purposes and applications. This paper uses PSO and GWO to select features for the intrusion detection system.… More >

Mohammad Monirujjaman Khan^1,*, Shamsun Nahar Safa¹, Minhazul Hoque Ashik¹, Mehedi Masud², Mohammed A. AlZain³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 49-64, 2021, DOI:10.32604/iasc.2021.016077

Abstract Smart wheelchairs play a significant role in supporting disabled people. Individuals with motor function impairments due to some disorders such as strokes or multiple sclerosis face frequent moving difficulties. Hence, they need constant support from an assistant. This paper presents a brain-controlled wheelchair model to assist disabled and paralyzed patients. The wheelchair is controlled by interpreting Electroencephalogram (EEG) signals, also known as brain waves. In the EEG technique, an electrode cap is positioned on the user’s scalp to receive EEG signals, which are detected and transformed by the Arduino microcontroller into motion commands, which drive the wheelchair. The proposed wheelchair… More >

Sobia Wassan¹, Chen Xi^1,*, Nz Jhanjhi², Hassan Raza³

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 187-199, 2021, DOI:10.32604/iasc.2021.015859

Abstract Online banking is an ideal method for conducting financial transactions such as e-commerce, e-banking, and e-payments. The growing popularity of online payment services and payroll systems, however, has opened new pathways for hackers to steal consumers’ information and money, a risk which poses significant danger to the users of e-commerce and e-banking websites. This study uses the selection method of the entire e-commerce and e-banking website dataset (Chi-Squared, Gini index, and main learning algorithm). The results of the analysis suggest the identification and comparison of machine learning and deep learning algorithm performance on binary category labels (legal, fraudulent) between similar… More >

Maryam Munawar, Iram Noreen^*

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 927-937, 2021, DOI:10.32604/iasc.2021.018854

Abstract Video and image data is the most important and widely used format of communication today. It is used as evidence and authenticated proof in different domains such as law enforcement, forensic studies, journalism, and others. With the increase of video applications and data, the problem of forgery in video and images has also originated. Although a lot of work has been done on image forgery, video forensic is still a challenging area. Videos are manipulated in many ways. Frame insertion, deletion, and frame duplication are a few of the major challenges. Moreover, in the perspective of duplicated frames, frame rate… More >

Hanan A. Hosni Mahmoud^*, Amal H. Alharbi, Doaa S. Khafga

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 803-814, 2021, DOI:10.32604/iasc.2021.018607

Abstract In this paper, we aim to apply deep learning convolution neural network (Deep-CNN) technology to classify breast masses in mammograms. We develop a Deep-CNN combined with multi-feature extraction and transfer learning to detect breast cancer. The Deep-CNN is utilized to extract features from mammograms. A support vector machine (SVM) is then trained on the Deep-CNN features to classify normal, benign, and cancer cases. The scoring features from the Deep-CNN are coupled with texture features and used as inputs to the final classifier. Two texture features are included: texture features of spatial dependency and gradient-based histograms. Both are employed to locate… More >

A. M. Abdullah¹, Hegazy Rezk^2,3,*, Abdelrahman Elbloye¹, Mohamed K. Hassan^1,4, A. F. Mohamed^1,5

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 729-740, 2021, DOI:10.32604/iasc.2021.018595

Abstract The energy harvested from a thermoelectric generator (TEG) relies mostly on the difference in temperature between the hot side and cold side of the TEG along with the connected load. Hence, a reliable maximum power point tracker is needed to force the TEG to operate close to the maximum power point (MPP) with any variation during the operation. In the current work, an optimized fractional maximum power point tracker (OFMPPT) is proposed to improve the performance of the TEG. The proposed tracker is based on fractional control. The optimal parameters of the OFMPPT have been determined using the grey wolf… More >

Toqir A. Rana^1,*, Bahrooz Bakht¹, Mehtab Afzal¹, Natash Ali Mian², Muhammad Waseem Iqbal³, Abbas Khalid¹, Muhammad Raza Naqvi⁴

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 839-853, 2021, DOI:10.32604/iasc.2021.018572

Abstract Opinion target or aspect extraction is the key task of aspect-based sentiment analysis. This task focuses on the extraction of targeted words or phrases against which a user has expressed his/her opinion. Although, opinion target extraction has been studied extensively in the English language domain, with notable work in other languages such as Chinese, Arabic etc., other regional languages have been neglected. One of the reasons is the lack of resources and available texts for these languages. Urdu is one, with millions of native and non-native speakers across the globe. In this paper, the Urdu language domain is focused on… More >

D. Saber^1,*, Ibrahim B. M. Taha², Kh. Abd El-Aziz³

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 757-769, 2021, DOI:10.32604/iasc.2021.018516

Abstract In this study, optimal regression learner methods were used to predict the corrosion behavior of aluminum–silicon alloys (Al–Si) with various Si ratios in different media. Al–Si alloys with 0, 1%, 8%, 11.2%, and 15% Si were tested in different media with different pH values at different stirring speeds (0, 300, 600, 750, 900, 1050, and 1200 rpm). Corrosion behavior was evaluated via electrochemical potentiodynamic test. The corrosion rates (CRs) obtained from the corrosion tests were utilized in the formation of datasets of various machine regression learner optimization (MRLO) methods, namely, decision tree, support vector machine, Gaussian process regression, and ensemble… More >

Xiaoliang Lin^1,*, Junxiao Shi¹, Yanbo Wang¹, Chenyang Liu¹, Bin Lu¹, Siwen Xu²

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 915-926, 2021, DOI:10.32604/iasc.2021.018513

Abstract Internet of Vehicles (IoV) is a popular application scenario that combines edge computing and the Internet of Things. Among them, service migration caused by IoV application mobility is a research hotspot in this field. This paper studies the migration strategy of container applications based on edge computing in the IoV business scenario. In order to solve the difficulty in selecting the target server of the application to be migrated in the crossroads scenario, this paper converts the migration decision to the shortest path problem based on dynamic programming, and obtains the best migration choice at the current time by finding… More >