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 >

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

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 inversion accuracy and the influence… 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

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) algorithm with benchmark machine-learning classifiers… More >

Munif Alotaibi^1,*, Bandar Alotaibi²

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

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 negative rate and needs a… More >

Ting-Hsuan Chien^1,*, Cheng-Yan Siao², Rong-Guey Chang²

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 827-838, 2021, DOI:10.32604/iasc.2021.018256

Abstract This paper describes a real-time simulator that allows the user in the factories to simulate arbitrary interaction between machinery and equipment. We discussed in details not only the general technique for developing such a real-time simulator but also the implementation of the simulator in its actual use. As such, people on the production line could benefit from observing and controlling robots in factories for preventing or reducing the severity of a collision, using the proposed simulator and its related technique. For that purpose, we divided the simulator into two main models: the real-time communication model and the simulation model. For… More >

Jhe-Wei Lin¹, Cheng-Yan Siao¹, Ting-Hsuan Chien^2,*, Rong-Guey Chang¹

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 685-695, 2021, DOI:10.32604/iasc.2021.018254

Abstract Since the rapid growth of the Fourth Industrial Revolution (or Industry 4.0), robots have been widely used in many applications. In the catering industry, robots are used to replace people to do routine jobs. Because meal is an important part of the catering industry, we aim to design and develop a robot to deliver meals for saving cost and improving a restaurant’s performance in this paper. However, for the existing meal delivery system, the guests must make their meals by themselves. To let the food delivery system become more user-friendly, we integrate an automatic guided vehicle (AGV) and a robotic… More >

Mengyuan Liao¹, Jing Duan^2,3,*, Rong Zhang^2,3, Xu Zhou^2,3, Xi Wu¹, Xin Wang⁴, Jinrong Hu¹

Intelligent Automation & Soft Computing, Vol.29, No.3, pp. 787-801, 2021, DOI:10.32604/iasc.2021.018190

Abstract In the field of weather modification, it is important to accurately identify the ice crystal particles in ice clouds. When ice crystal habits are correctly identified, cloud structure can be further understood and cloud seeding and other methods of weather modification can be used to change the microstructure of the cloud. Consequently, weather phenomena can be changed at an appropriate time to support human production and quality of life. However, ice crystal morphology is varied. Traditional ice crystal particle classification methods are based on expert experience, which is subjective and unreliable for the identification of the categories by threshold setting.… More >