Zihai Geng^1,2,*, Jinsheng Cai¹, Yubiao Jiang^1,2, Weiguo Zhang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.5, pp. 899-915, 2021, DOI:10.32604/fdmp.2021.012108 - 05 July 2021

Abstract Reducing drag during take-off and nominal (cruise) conditions is a problem of fundamental importance in aeronautical engineering. Existing studies have demonstrated that v-shaped symmetrical riblets can effectively be used for turbulence control, with those with dimensionless depth h⁺ = 15 and dimensionless width s⁺ = 15 having the best drag reduction effect. In the present study, experimental tests have been conducted considering two models of the same size, one with smooth surface, the other with v-shaped riblets of the h⁺ = 15 and s⁺ = 15 type. The results show that for an angle of attack in More >

Maryam Munawar, Iram Noreen^*

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 927-937, 2021, DOI:10.32604/iasc.2021.018854 - 01 July 2021

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… 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 - 01 July 2021

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.… 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 - 01 July 2021

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… 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 - 01 July 2021

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… 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 - 01 July 2021

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,… 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 - 01 July 2021

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 More >

Tao Li¹, Ning Peng Li¹, Qi Qian¹, Wen Duo Xu¹, Yong Jun Ren^2,*, Jin Yue Xia³

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 741-755, 2021, DOI:10.32604/iasc.2021.018496 - 01 July 2021

Abstract In this paper, the inversion method of atmospheric temperature and humidity profiles via ground-based microwave radiometer is studied. Using the three-layer BP neural network inversion algorithm, four BP neural network models (temperature and humidity models with and without cloud information) are established using L-band radiosonde data obtained from the Atmospheric Exploration base of the China Meteorological Administration from July 2018 to June 2019. Microwave radiometer level 1 data and cloud radar data from July to September 2019 are used to evaluate the model. The four models are compared with the measured sounding data, and the More >

Bushra Mumtaz¹, Summrina Kanwal^2,*, Sultan Alamri², Faiza Khan¹

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 669-684, 2021, DOI:10.32604/iasc.2021.018405 - 01 July 2021

Abstract Software Defect Prediction (SDP) is a dynamic research field in the software industry. A quality software product results in customer satisfaction. However, the higher the number of user requirements, the more complex will be the software, with a correspondingly higher probability of failure. SDP is a challenging task requiring smart algorithms that can estimate the quality of a software component before it is handed over to the end-user. In this paper, we propose a hybrid approach to address this particular issue. Our approach combines the feature selection capability of the Optimized Artificial Immune Networks (Opt-aiNet) More >

Munif Alotaibi^1,*, Bandar Alotaibi²

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 885-898, 2021, DOI:10.32604/iasc.2021.018350 - 01 July 2021

Abstract The novel coronavirus 2019 (COVID-19) is one of a large family of viruses that cause illness, the symptoms of which range from a common cold, fever, coughing, and shortness of breath to more severe symptoms. The virus rapidly and easily spreads from infected people to others through close contact in the absence of protection. Early detection of COVID-19 assists governmental authorities and healthcare specialists in reducing the chain of transmission and flattening the curve of the pandemic. The widespread form of the COVID-19 diagnostic test lacks a high true positive rate and a low false… More >