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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 >

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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 >

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981

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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 >

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Ayesha Maqbool^1,*, Farkhanda Afzal², Tauseef Rana³, Alina Mirza⁴
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 653-667, 2021, DOI:10.32604/iasc.2021.017506
（This article belongs to the Special Issue: Nature Inspired Computing for Intelligent Vehicular Network)
Abstract This paper presents a co-operative, self-organisation method for Multiple Autonomous Vehicles aiming to share surveillance responsibilities. Spatial organization or formation configuration of multiple vehicles/agents’ systems is crucial for a team of agents to achieve their mission objectives. In this paper we present simple yet efficient thermodynamic inspired formation control framework. The proposed method autonomously allocates region of surveillance to each vehicle and also re-adjusts the area of their responsibilities during the mission. It provides framework for heterogeneous UAVs to scatter themselves optimally in order to provide maximum coverage of a given area. The method is inspired from a natural phenomenon… More >

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Anshu Parashar^*, Nidhi Kalra, Jaskirat Singh, Raman Kumar Goyal
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 669-682, 2021, DOI:10.32604/iasc.2021.017478
Abstract Electrophysiological (EEG) signals provide good temporal resolution and can be effectively used to assess and diagnose children with Attention Deficit Hyperactivity Disorder (ADHD). This study aims to develop a machine learning model to classify children with ADHD and Healthy Controls. In this study, EEG signals captured under cognitive tasks were obtained from an open-access database of 60 children with ADHD and 60 Healthy Controls children of similar age. The regional contributions towards attaining higher accuracy are identified and further tested using three classifiers: AdaBoost, Random Forest and Support Vector Machine. The EEG data from 19 channels is taken as input… More >

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1447

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Tingting Yang^1,*, Shuwen Jia¹, Boxiong Yang¹, Chenxi Kan²
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 683-692, 2021, DOI:10.32604/iasc.2021.017235
Abstract In the augmented reality system, the position and direction of the user’s point of view and line of sight in the real scene is acquired in real-time. The position and direction information will determine the exact position of the virtual object of the real scene. At the same time, various coordinate systems are established according to the user’s line of sight. So registration tracking technology is very important. The paper proposes an accurate, stable, and effective augmented reality registration algorithm. The method adopts the method of ORB (oriented FAST and rotated BRIEF) features matching combined with RANSAC (random sample consensus)… More >

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1070

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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
（This article belongs to the Special Issue: Soft Computing Methods for Innovative Software Practices)
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 >

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963

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Mohamed I. Mossad^1,*, Fahd A. banakhr¹, Sherif S. M. Ghoneim², Tarek A. AbdulFattah³, Mohamed Mahmoud Samy⁴
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 715-727, 2021, DOI:10.32604/iasc.2021.017534
（This article belongs to the Special Issue: Artificial Techniques: Application, Challenges, Performance Improvement of Smart Grid and Renewable Energy Systems)
Abstract This paper introduces voltage self-regulation of a variable speed single-phase induction generator-based wind energy conversion system (WECS) for stand-alone applications. The idea behind the voltage self-regulation technique proposed in this paper is adjusting the fixed capacitor’s effective value for exciting the single-phase induction generator. This adjustment is performed using an inexpensive Sinusoidal PWM (SPWM) switching circuit to short circuit the capacitor during different periods to make a virtual change of the capacitance value extracted from the fixed capacitor. That optimized fixed capacitor size is firstly determined using harmony search (HS) optimization technique. HS is also used to determine the capacitance… More >

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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 >

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1142

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Ibrahim B.M. Taha¹, Diaa-Eldin A. Mansour^2,*
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 739-752, 2021, DOI:10.32604/iasc.2021.017703
Abstract Power transformer is one of the more important components of electrical power systems. The early detection of transformer faults increases the power system reliability. Dissolved gas analysis (DGA) is one of the most favorite approaches used for power transformer fault prediction due to its easiness and applicability for online diagnosis. However, the imbalanced, insufficient and overlap of DGA dataset impose a challenge towards powerful and accurate diagnosis. In this work, a novel fault diagnosis for power transformers is introduced based on DGA by using data transformation and six optimized machine learning (OML) methods. Four data transformation techniques are used with… More >

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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
（This article belongs to the Special Issue: Machine Learning and Deep Learning for Transportation)
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 >

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Nehmdoh A. Sabiha^*, Hend I. Alkhammash
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 769-784, 2021, DOI:10.32604/iasc.2021.016752
（This article belongs to the Special Issue: Artificial Techniques: Application, Challenges, Performance Improvement of Smart Grid and Renewable Energy Systems)
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 >

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1154

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Jinrong Hu¹, Lujin Li¹, Wenyi Yang², Zhe Wang³, Junhui Wang⁴, Yan Zhu^5,*
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 785-795, 2021, DOI:10.32604/iasc.2021.017467
Abstract The meridian theory, as an essential part of Traditional Chinese Medicine (TCM) fundamentals, provides an explanation of the spatial and functional relationship between the superficial part and the internal organs based on empiric observations. Cutaneous regions which are the body superficies on which the functions of the meridians are reflected, and the sites where the qi of the collateral’s spreads, play an important role in TCM clinical diagnosis and treatment of skin diseases. The survey of the literature on anatomical site, pathology in patients with skin disease, particularly in TCM perspective, clearly indicates that a better cutaneous region model and… More >

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1314

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Hongshuo Zhang¹, Bo Zhu^1,*, Kaimin Pang¹, Chunmei Chen¹, Yuwei Wan²
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 797-810, 2021, DOI:10.32604/iasc.2021.017232
Abstract Using machine learning method to recognize abnormal patterns covers the shortage of traditional control charts for autocorrelation processes, which violate the applicable conditions of the control chart, i.e., the independent identically distributed (IID) assumption. In this study, we propose a recognition model based on support vector machine (SVM) for the AR (1) type of autocorrelation process. For achieving a higher recognition performance, the cuckoo search algorithm (CS) is used to optimize the two hyper-parameters of SVM, namely the penalty parameter c and the radial basis kernel parameter g. By using Monte Carlo simulation methods, the data sets containing samples of… More >

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1647

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930

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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 >

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963

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Khakoo Mal^1,2, Imtiaz Hussain Kalwar³, Khurram Shaikh², Tayab Din Memon^2,4, Bhawani Shankar Chowdhry¹, Kashif Nisar^5,*, Manoj Gupta⁶
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 823-841, 2021, DOI:10.32604/iasc.2021.016990
Abstract

The core part of any study of rolling stock behavior is the wheel-track interaction patch because the forces produced at the wheel-track interface govern the dynamic behavior of the whole railway vehicle. It is significant to know the nature of the contact force to design more effective vehicle dynamics control systems and condition monitoring systems. However, it is hard to find the status of this adhesion force due to its complexity, highly non-linear nature, and also affected with an unpredictable operation environment. The purpose of this paper is to develop a model-based estimation technique using the Extended Kalman Filter (EKF)… More >

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Mohammed Abaker^1,*, Abdelzahir Abdelmaboud², Magdi Osman³, Mohammed Alghobiri⁴, Ahmed Abdelmotlab⁴
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 843-856, 2021, DOI:10.32604/iasc.2021.017714
Abstract The rock-fall is a natural hazard that results in many economic damages and human losses annually, and thus proactive policies to prevent rock-fall hazard are needed. Such policies require predicting the rock-fall occurrence and deciding to alert the road users at the appropriate time. Thus, this study develops a rock-fall early warning system based on logistic regression model. In this system, the logistic regression model is used to predict the rock-fall occurrence. The decision-making algorithm is used to classify the hazard levels and delivers early warning action. This study adopts two criteria to evaluate the system predictive performance, including overall… More >

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2023

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1224

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Ming Wan¹, Shiyan Zhang¹, Yan Song², Jiangyuan Yao^3,*, Hao Luo¹, Xingcan Cao⁴
Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 857-871, 2021, DOI:10.32604/iasc.2021.017214
Abstract Due to the lack of security consideration in the original design of industrial communication protocols, industrial fuzzing test which can successfully exploit various potential security vulnerabilities has become one new research hotspot. However, one critical issue is how to improve its testing efficiency. From this point of view, this paper proposes a novel fuzzing test case optimization approach based on improved genetic algorithm for industrial communication protocols. Moreover, a new individual selection strategy is designed as the selection operator in this genetic algorithm, which can be actively engaged in the fuzzing test case optimization process. In this individual selection strategy,… More >

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934

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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 >

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883

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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
（This article belongs to the Special Issue: Machine Learning and Deep Learning for Transportation)
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 >

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