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 >

Arkan Kh Shakr Sabonchi^*, Bahriye Akay

Computer Systems Science and Engineering, Vol.39, No.1, pp. 87-106, 2021, DOI:10.32604/csse.2021.05365

Abstract This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms… More >

Amer Ibrahim Al-Omari¹, Ayed R.A. Alanzi^2,*

Computer Systems Science and Engineering, Vol.39, No.1, pp. 147-164, 2021, DOI:10.32604/csse.2021.017362

Abstract In this paper, we suggested and studied the inverse length biased Maxell distribution (ILBMD) as a new continuous distribution of one parameter. The ILBMD is obtained by considering the inverse transformation technique of the Maxwell length biased distribution. Statistical characteristics of the ILBMD such as the moments, moment generating function, mode, quantile function, the coefficient of variation, coefficient of skewness, Moors and Bowley measures of kurtosis and skewness , stochastic ordering, stress-strength reliability, and mean deviations are obtained. In addition, the Bonferroni and Lorenz curves, Gini index, the reliability function, the hazard rate function, the reverse hazard rate function, the… More >

Zhenyu Tang¹, Jin Liu^1,*, Chao Yu¹, Y. Ken Wang²

Computer Systems Science and Engineering, Vol.39, No.1, pp. 37-54, 2021, DOI:10.32604/csse.2021.017230

Abstract The subtitle recognition under multimodal data fusion in this paper aims to recognize text lines from image and audio data. Most existing multimodal fusion methods tend to be associated with pre-fusion as well as post-fusion, which is not reasonable and difficult to interpret. We believe that fusing images and audio before the decision layer, i.e., intermediate fusion, to take advantage of the complementary multimodal data, will benefit text line recognition. To this end, we propose: (i) a novel cyclic autoencoder based on convolutional neural network. The feature dimensions of the two modal data are aligned under the premise of stabilizing… More >

Yousef Sanajalwe^1,2,*, Mohammed Anbar¹, Salam Al-E’mari¹

Computer Systems Science and Engineering, Vol.39, No.1, pp. 15-35, 2021, DOI:10.32604/csse.2021.017191

Abstract The novel coronavirus disease 2019 (COVID-19) is a pandemic disease that is currently affecting over 200 countries around the world and impacting billions of people. The first step to mitigate and control its spread is to identify and isolate the infected people. But, because of the lack of reverse transcription polymerase chain reaction (RT-CPR) tests, it is important to discover suspected COVID-19 cases as early as possible, such as by scan analysis and chest X-ray by radiologists. However, chest X-ray analysis is relatively time-consuming since it requires more than 15 minutes per case. In this paper, an automated novel detection… More >

Jingjun Zhou^1,2, Jing Liu³, Jingbing Li^1,2,*, Mengxing Huang^1,2, Jieren Cheng⁴, Yen-Wei Chen⁵, Yingying Xu^3,6, Saqib Ali Nawaz¹

Computer Systems Science and Engineering, Vol.39, No.1, pp. 133-146, 2021, DOI:10.32604/csse.2021.016633

Abstract Recent applications of convolutional neural networks (CNNs) in single image super-resolution (SISR) have achieved unprecedented performance. However, existing CNN-based SISR network structure design consider mostly only channel or spatial information, and cannot make full use of both channel and spatial information to improve SISR performance further. The present work addresses this problem by proposing a mixed attention densely residual network architecture that can make full and simultaneous use of both channel and spatial information. Specifically, we propose a residual in dense network structure composed of dense connections between multiple dense residual groups to form a very deep network. This structure… More >

Wenjun Gao¹, Yang Yang^1,*, Hongtao Duan¹, Mingsheng Li¹, Jinrong Ma¹, Songwei Jin²

Computer Systems Science and Engineering, Vol.39, No.1, pp. 69-85, 2021, DOI:10.32604/csse.2021.016475

Abstract The two-dimensional (2-D) system has a wide range of applications in different fields, including satellite meteorological maps, process control, and digital filtering. Therefore, the research on the stability of 2-D systems is of great significance. Considering that multiple systems exist in switching and alternating work in the actual production process, but the system itself often has external perturbation and interference. To solve the above problems, this paper investigates the output feedback robust H_∞ stabilization for a class of discrete-time 2-D switched systems, which the Roesser model with uncertainties represents. First, sufficient conditions for exponential stability are derived via the average… More >

Chengchen Zhuge^1,2,3,*, Qun Wang^1,2,3, Jiayin Liu^1,2,3, Lingxiang Yao⁴

Computer Systems Science and Engineering, Vol.39, No.1, pp. 107-119, 2021, DOI:10.32604/csse.2021.016273

Abstract The Rapidly-exploring Random Tree (RRT) algorithm is an efficient path-planning algorithm based on random sampling. The RRT* algorithm is a variant of the RRT algorithm that can achieve convergence to the optimal solution. However, it has been proven to take an infinite time to do so. An improved Quick-RRT* (Q-RRT*) algorithm based on a virtual light source is proposed in this paper to overcome this problem. The virtual light-based Q-RRT* (LQ-RRT*) takes advantage of the heuristic information generated by the virtual light on the map. In this way, the tree can find the initial solution quickly. Next, the LQ-RRT* algorithm… More >