A. Manjula^1,*, L. Kalaivani², M. Gengaraj²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 451-465, 2021, DOI:10.32604/iasc.2021.016088

Abstract The fast-growing field of mechanical robotization necessitates a well-designed and controlled version of electric drives. The concept of control concerning mechanical characteristics also requires a methodology in which the system needs to be modeled precisely and deals with uncertainty. The proposed method provides the enhanced performance of Switched Reluctance Motor (SRM) by controlling its speed and minimized torque ripple. Proportional-Integral-Derivative (PID) controllers have drawn more attention in industry automation due to their ease and robustness. The performances are further improved by using fractional order (Non-integer) controllers. The Modified Particle Swarm Optimization (MPSO) based optimization approach is employed to acquire the… More >

Adnan Bin Amanat Ali¹, Vasaki Ponnusamy¹, Anbuselvan Sangodiah¹, Roobaea Alroobaea², N. Z. Jhanjhi^3,*, Uttam Ghosh⁴, Mehedi Masud²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 571-585, 2021, DOI:10.32604/iasc.2021.015913

Abstract Most smartphone users prefer easy and convenient authentication without remembering complicated passwords or drawing intricate patterns. Preferably, after one-time authentication, there is no verification of the user’s authenticity. Therefore, security and privacy against unauthorized users is a crucial research area. Behavioral authentication is an emerging security technique that is gaining attention for its uniqueness and transparency. In this paper, a behavior-based authentication system is built using swipe movements to continuously authenticate the user after one-time traditional authentication. The key feature is the selection of an optimal feature set for the swipe movement. Five machine learning classifiers are used, of which… More >

Kentaro Mori^1,*, Kotaro Kitaya², Tomomoto Ishikawa², Yutaka Hata³

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 335-352, 2021, DOI:10.32604/iasc.2021.01010

Abstract In infertility treatment, it is required to improve a success rate of the treatment. A purpose of this study is to develop a prediction system for pregnancy outcomes using ultrasonic images. In infertility treatment, it is typical to evaluate the endometrial shape by using ultrasonic images. The convolutional neural network (CNN) system developed in the current study predicted pregnancy outcome by velocity information. The velocity information has a movement feature of uterine. It is known that a uterine movement is deep related to infertility. Experiments compared the velocity-based and shape-based systems. The shape-based systems predict the optimal uterine features for… More >

Abdelatif Oussar^1,*, Abdelmoumen Ferrag¹, Mohamed Guiatni¹, Mustapha Hamerlain²

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 467-495, 2021, DOI:10.32604/iasc.2021.01000

Abstract This paper presents the design of a robust architecture for the tracking of an unmanned ground vehicle (UGV) by an unmanned aerial vehicle (UAV). To enhance the robustness of the ground vehicle in the face of external disturbances and handle the non-linearities due to inputs saturation, an integral sliding mode controller was designed for the task of trajectory tracking. Stabilization of the aerial vehicle is achieved using an integral-backstepping solution. Estimation of the relative position between the two agents was solved using two approaches: the first solution (optimal) is based on a Kalman filter (KF) the second solution (robust) uses… More >

Abdelaziz Alsubie¹, Mostafa Abdelhamid², Abdul Hadi N. Ahmed², Mohammed Alqawba³, Ahmed Z. Afify^4,*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 213-232, 2021, DOI:10.32604/iasc.2021.018111

Abstract In this paper, the estimation of the parameters of extended Marshall-Olkin inverse-Pareto (EMOIP) distribution is studied under complete and censored samples. Five classical methods of estimation are adopted to estimate the parameters of the EMOIP distribution from complete samples. These classical estimators include the percentiles estimators, maximum likelihood estimators, least squares estimators, maximum product spacing estimators, and weighted least-squares estimators. The likelihood estimators of the parameters under type-I and type-II censoring schemes are discussed. Simulation results were conducted, for various parameter combinations and different sample sizes, to compare the performance of the EMOIP estimation methods under complete and censored samples.… More >

Abdullah Ali H. Ahmadini¹, Amal Hassan², M. Elgarhy^3,*, Mahmoud Elsehetry⁴, Shokrya S. Alshqaq⁵, Said G. Nassr⁶

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 199-212, 2021, DOI:10.32604/iasc.2021.017890

Abstract This paper introduces a modified form of the inverse Lomax distribution which offers more flexibility for modeling lifetime data. The new three-parameter model is provided as a member of the truncated Lomax-G procedure. The new modified distribution is called the truncated Lomax inverse Lomax distribution. The density of the new model can be represented as a linear combination of the inverse Lomax distribution. Expansions for quantile function, moment generating function, probability weighted moments, ordinary moments, incomplete moments, inverse moments, conditional moments, and Rényi entropy measure are investigated. The new distribution is capable of monotonically increasing, decreasing, reversed J-shaped and upside-down… More >

Ahmad Almufarreh, Muhammad Arshad^*, Sameer Hassan Mohammed

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 73-87, 2021, DOI:10.32604/iasc.2021.017803

Abstract Without the constraints of time and place, e-learning can offer a strong learning environment. The notion of e-learning has taken on a new sense with the advent and popularization of mobile devices and ubiquitous computing, enabling students to have access to several diverse opportunities for communicating with e-learning programs. Around the same time, it has prompted the course’s planners to select the most suitable technology from among the various innovations required for the storing and dissemination of information representation. As a Learning Management System (LMS), the Blackboard system now has a recognized role in the knowledge management of the education… More >

Pengfei Gong^1,2, Qun Wang^2,*, Junjun Zhu³

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 31-42, 2021, DOI:10.32604/iasc.2021.017695

Abstract This study analyzed in-depth investigation reports for 418 traffic accidents with at least five deaths (TALFDs) in China from 2016 to 2019. Statistical analysis methods including hierarchical cluster analysis were employed to examine the distribution characteristics of these accidents. Accidents were found to be concentrated in July and August, and the distribution over the seven days of the week was relatively uniform; only Sunday had a higher number of accidents and deaths. In terms of 24-hour distribution, the one-hour periods with the most accidents and deaths were 8:00–9:00, 10:00–11:00, 14:00–15:00, and 18:00–19:00. Tibet, Qinghai, and Ningxia had the highest death… More >

Abdullah Ali H. Ahmadini¹, Amal S. Hassan², Rokaya E. Mohamed^3,*, Shokrya S. Alshqaq⁴, Heba F. Nagy⁵

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 131-146, 2021, DOI:10.32604/iasc.2021.017652

Abstract In this research article, we propose and study a new model the so-called Marshal-Olkin Kumaraswamy moment exponential distribution. The new distribution contains the moment exponential distribution, exponentiated moment exponential distribution, Marshal Olkin moment exponential distribution and generalized exponentiated moment exponential distribution as special sub-models. Some significant properties are acquired such as expansion for the density function and explicit expressions for the moments, generating function, Bonferroni and Lorenz curves. The probabilistic definition of entropy as a measure of uncertainty called Shannon entropy is computed. Some of the numerical values of entropy for different parameters are given. The method of maximum likelihood… More >

Osama S. Faragallah^1,*, Ghada Abdel-Aziz², Walid El-Shafai³, Hala S. El-sayed⁴, S.F. El-Zoghdy⁵, Gamal G.N. Geweid^6,7

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 15-29, 2021, DOI:10.32604/iasc.2021.017616

Abstract The process of segmentation of the cardiac image aims to limit the inner and outer walls of the heart to segment all or portions of the organ’s boundaries. Due to its accurate morphological information, magnetic resonance (MR) images are typically used in cardiac segmentation as they provide the best contrast of soft tissues. The data acquired from the resulting cardiac images simplifies not only the laboratory assessment but also other conventional diagnostic techniques that provide several useful measures to evaluate and diagnose cardiovascular disease (CVD). Therefore, scientists have offered numerous segmentation schemes to remedy these issues for producing more accurate… More >