V. Nivedhitha^1,*, A. Gopi Saminathan², P. Thirumurugan³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 603-616, 2021, DOI:10.32604/iasc.2021.016780

Abstract Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and the distance of sensor nodes… More >

Nehmdoh A. Sabiha^*, Hend I. Alkhammash

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 769-784, 2021, DOI:10.32604/iasc.2021.016752

Abstract The maximum temperature that cable insulation can withstand determines the maximum load that the cable conductor can carry, which is called cable ampacity. However, a temperature far from this value under normal load conditions affects the transients due to earth faults in the distribution network. Accordingly, error estimation in the fault location occurs, and the smart grids do not accept such errors. Considering heterogenous unearthed and compensated distribution networks, the temperature rise in different underground cables is estimated under different load conditions. These loads are full load, three quarters (3/4) load, one half (1/2) load, and one quarter (1/4) load.… More >

Wael Alosaimi¹, Rajeev Kumar^2,*, Abdullah Alharbi¹, Hashem Alyami³, Alka Agrawal⁴, Gaurav Kaithwas⁵, Sanjay Singh⁶, Raees Ahmad Khan⁴

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 617-628, 2021, DOI:10.32604/iasc.2021.016703

Abstract COVID-19 pandemic has unleashed an unprecedented humanitarian crisis in the world at present. With each passing day, the number of patients afflicted with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is rising at an alarming pace, so much so that some countries are now combating the second wave of the contagion. As the death ratio due to the Virus increases, the medical fraternity and pharmacologists are working relentlessly to identify and prescribe a standardized and effective course of treatment for treating COVID-19 patients. However, medical specialists are confused about opting for the most efficacious course of treatment because the patients… More >

Muhammad Shaheen^1,*, Ali Ahsan², Saeed Iqbal³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 873-885, 2021, DOI:10.32604/iasc.2021.016622

Abstract While there are several Scientometrics that can be used to assess the quality of the scientific work published in journals and conferences, yet; their validity and suitability is a great concern for stakeholders from both academia and industry. Different organizations have a different set of criteria for assessing the journals publishing scientific content. This is mostly based on the information generated from Scientometrics. A unified journal ranking system is therefore required that is acceptable to all concerned. This paper, collects data concerning Scientometrics for unified assessment of journals and proposes a mechanism of assessment using data mining methods. In order… More >

Ye Mu^1,2,3,4, Yuheng Sun¹, Tianli Hu^1,2,3,4, He Gong^1,2,3,4, Shijun Li^1,2,3,4,*, Thobela Louis Tyasi⁵

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 729-737, 2021, DOI:10.32604/iasc.2021.016569

Abstract The rapid development of computer vision technology and digital images has increased the potential for using image recognition for eye disease diagnosis. Many early screening and diagnosis methods for ocular diseases based on retinal images of the fundus have been proposed recently, but their accuracy is low. Therefore, it is important to develop and evaluate an improved VGG model for the recognition and classification of retinal fundus images. In response to these challenges, to solve the problem of accuracy and reliability of clinical algorithms in medical imaging this paper proposes an improved model for early recognition of ophthalmopathy in retinal… More >

Zhengzheng Li¹, Jiancheng Zou^2,*, Peizhou Yan¹, Don Hong³

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 811-822, 2021, DOI:10.32604/iasc.2021.016516

Abstract Real-time and effective monitoring of a driver’s physiological parameters and psychological states can provide early warnings and help avoid traffic accidents. In this paper, we propose a non-contact real-time monitoring algorithm for physiological parameters of drivers under ambient light conditions. First, video sequences of the driver’s head are obtained by an ordinary USB camera and the AdaBoost algorithm is used to locate the driver’s facial region. Second, a face expression recognition algorithm based on an improved convolutional neural network (CNN) is proposed to recognize the driver’s facial expression. The forehead region is divided into three RGB channels as the region… More >

Salah K. Elsayed^1,*, Ahmed M. Agwa^2,3, Mahmoud A. El-Dabbah², Ehab E. Elattar¹

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 639-651, 2021, DOI:10.32604/iasc.2021.016464

Abstract The problem of parameters identification for transformer equivalent circuit can be solved by optimizing a nonlinear formula. The objective function attempts to minimize the sum of squared relative errors amongst the accompanying calculated and actual points of currents, powers, and secondary voltage during the load test of the transformer subject to a set of parameters constraints. The authors of this paper propose applying a new and efficient stochastic optimizer called the slime mold optimization algorithm (SMOA) to identify parameters of the transformer equivalent circuit. The experimental measurements of load test of single- and three-phase transformers are entered to MATLAB code… More >

Islam Ali¹, Wasif Nisar¹, Waqar Mehmood², Muhammad Qaiser Saleem³, Ali S. Ahmed³, Haysam E. Elamin⁴, Mahmood Niazi⁵, Muhammad Shafiq^6,*

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 693-713, 2021, DOI:10.32604/iasc.2021.016381

Abstract Capability Maturity Model Integration (CMMI) is used for Software Process Improvement (SPI) worldwide. Research reveals that CMMI adoption needs a lot of resources in terms of training, funds, and professional workers. Software Small & Medium Enterprises (SSMEs) cannot, however, reserve resources for the purpose. One of the challenges of CMMI adoption is that CMMI identifies “What-to-Do” as a requirement to fulfill and leaves “How-To-Do” to implementers. Implementation of Configuration Management Process Area (CM-PA), being one of the umbrella activities, presents more obstacles generally to the software industry and particularly to SSMEs as compared to other PAs. Establish software baselines is… More >

Meenakshi Malik¹, Rainu Nandal¹, Surjeet Dalal², Vivek Jalglan³, Dac-Nhuong Le^4,5,*

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 887-906, 2021, DOI:10.32604/iasc.2021.016272

Abstract The last several decades have witnessed an exponential growth in the means of transport globally, shrinking geographical distances and connecting the world. The automotive industry has grown by leaps and bounds, with millions of new vehicles being sold annually, be it for personal commuting or for public or commodity transport. However, millions of motor vehicles on the roads also mean an equal number of drivers with varying levels of skill and adherence to safety regulations. Very little has been done in the way of exploring and profiling driving patterns and vehicular usage using real world data. This paper focuses on… More >

Fulu Wei^1,2, Zhenggan Cai¹, Yongqing Guo^1,*, Pan Liu², Zhenyu Wang³, Zhibin Li²

Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 753-767, 2021, DOI:10.32604/iasc.2021.014661

Abstract The differences in traffic accident severity between urban and rural areas have been widely studied, but conclusions are still limited. To explore the factors influencing the occurrence of roadside accidents in urban and rural areas, 3735 roadside traffic accidents from 2017 to 2019 were analyzed. Fourteen variables from the aspects of driver, vehicle, driving environment, and other influencing factors were selected to establish a Bayesian binary logit model of roadside crashes. The deviance information criterion and receiver operating characteristic curve were used to test the goodness of fit for the traffic crash model. The results show that: (1) the Bayesian… More >