Saleem Mustafa¹, Arfan Jaffar¹, Muhammad Waseem Iqbal^2,*, Asma Abubakar², Abdullah S. Alshahrani³, Ahmed Alghamdi⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2205-2218, 2023, DOI:10.32604/iasc.2023.029549 - 19 July 2022

Abstract Melanoma is of the lethal and rare types of skin cancer. It is curable at an initial stage and the patient can survive easily. It is very difficult to screen all skin lesion patients due to costly treatment. Clinicians are requiring a correct method for the right treatment for dermoscopic clinical features such as lesion borders, pigment networks, and the color of melanoma. These challenges are required an automated system to classify the clinical features of melanoma and non-melanoma disease. The trained clinicians can overcome the issues such as low contrast, lesions varying in size,… More >

K. Santosh Jhansi^1,2,*, P. Ravi Kiran Varma², Sujata Chakravarty³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6327-6345, 2022, DOI:10.32604/cmc.2022.030878 - 28 July 2022

Abstract Malware Security Intelligence constitutes the analysis of applications and their associated metadata for possible security threats. Application Programming Interfaces (API) calls contain valuable information that can help with malware identification. The malware analysis with reduced feature space helps for the efficient identification of malware. The goal of this research is to find the most informative features of API calls to improve the android malware detection accuracy. Three swarm optimization methods, viz., Ant Lion Optimization (ALO), Cuckoo Search Optimization (CSO), and Firefly Optimization (FO) are applied to API calls using auto-encoders for identification of most influential More >

Sakda Noinang¹, Zulqurnain Sabir², Gilder Cieza Altamirano³, Muhammad Asif Zahoor Raja⁴, Manuel Jesús Sànchez-Chero⁵, María-Verónica Seminario-Morales⁵, Wajaree Weera^6,*, Thongchai Botmart⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437 - 28 July 2022

Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using More >

Mir Mushhood Afsar¹, Shizza Saqib¹, Yazeed Yasin Ghadi², Suliman A. Alsuhibany³, Ahmad Jalal¹, Jeongmin Park^4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4763-4777, 2022, DOI:10.32604/cmc.2022.028618 - 28 July 2022

Abstract Virtual reality is an emerging field in the whole world. The problem faced by people today is that they are more indulged in indoor technology rather than outdoor activities. Hence, the proposed system introduces a fitness solution connecting virtual reality with a gaming interface so that an individual can play first-person games. The system proposed in this paper is an efficient and cost-effective solution that can entertain people along with playing outdoor games such as badminton and cricket while sitting in the room. To track the human movement, sensors Micro Processor Unit (MPU6050) are used… More >

Thongchai Botmart¹, Wajaree Weera^1,*, Muhammad Asif Zahoor Raja², Zulqurnain Sabir³, Qusain Hiader⁴, Gilder Cieza Altamirano⁵, Plinio Junior Muro Solano⁶, Alfonso Tesen Arroyo⁶

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 981-999, 2022, DOI:10.32604/cmc.2022.028921 - 18 May 2022

Abstract In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order… More >

Muhammad Zubair Rehman¹, Muhammad Aamir^2,*, Nazri Mohd. Nawi³, Abdullah Khan⁴, Saima Anwar Lashari⁵, Siyab Khan⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 493-511, 2022, DOI:10.32604/cmc.2022.021787 - 18 May 2022

Abstract

Recently, many researchers have used nature inspired metaheuristic algorithms due to their ability to perform optimally on complex problems. To solve problems in a simple way, in the recent era bat algorithm has become famous due to its high tendency towards convergence to the global optimum most of the time. But, still the standard bat with random walk has a problem of getting stuck in local minima. In order to solve this problem, this research proposed bat algorithm with levy flight random walk. Then, the proposed Bat with Levy flight algorithm is further hybridized with

… More >

Muhammad Umar¹, Fazli Amin¹, Soheil Salahshour², Thongchai Botmart³, Wajaree Weera³, Prem Junswang^4,*, Zulqurnain Sabir¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6185-6202, 2022, DOI:10.32604/cmc.2022.027970 - 21 April 2022

Abstract The present study is related to design a stochastic framework for the numerical treatment of the Van der Pol heartbeat model (VP-HBM) using the feedforward artificial neural networks (ANNs) under the optimization of particle swarm optimization (PSO) hybridized with the active-set algorithm (ASA), i.e., ANNs-PSO-ASA. The global search PSO scheme and local refinement of ASA are used as an optimization procedure in this study. An error-based merit function is defined using the differential VP-HBM form as well as the initial conditions. The optimization of the merit function is accomplished using the hybrid computing performances of More >

Prem Junswang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Waleed Adel^4,5, Thongchai Botmart^6,*, Wajaree Weera⁶

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5015-5030, 2022, DOI:10.32604/cmc.2022.027523 - 21 April 2022

Abstract The purpose of this paper is to present a numerical approach based on the artificial neural networks (ANNs) for solving a novel fractional chaotic financial model that represents the effect of memory and chaos in the presented system. The method is constructed with the combination of the ANNs along with the Levenberg-Marquardt backpropagation (LMB), named the ANNs-LMB. This technique is tested for solving the novel problem for three cases of the fractional-order values and the obtained results are compared with the reference solution. Fifteen numbers neurons have been used to solve the fractional-order chaotic financial More >

Hyun Yoo¹, Kyungyong Chung^2,*

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 1-13, 2022, DOI:10.32604/iasc.2022.024890 - 15 April 2022

Abstract Human pose estimation has been a major concern in the field of computer vision. The existing method for recognizing human motion based on two-dimensional (2D) images showed a low recognition rate owing to motion depth, interference between objects, and overlapping problems. A convolutional neural network (CNN) based algorithm recently showed improved results in the field of human skeleton detection. In this study, we have combined human skeleton detection and deep neural network (DNN) to classify the motion of the human body. We used the visual geometry group network (VGGNet) CNN for human skeleton detection, and More >

Zulqurnain Sabir¹, Abeer S. Alnahdi^2,*, Mdi Begum Jeelani², Mohamed A. Abdelkawy^2,3,*, Muhammad Asif Zahoor Raja⁴, Dumitru Baleanu^5,6, Muhammad Mubashar Hussain⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 763-785, 2022, DOI:10.32604/cmes.2022.018496 - 14 March 2022

Abstract The present investigations are associated with designing Morlet wavelet neural network (MWNN) for solving a class of susceptible, infected, treatment and recovered (SITR) fractal systems of COVID-19 propagation and control. The structure of an error function is accessible using the SITR differential form and its initial conditions. The optimization is performed using the MWNN together with the global as well as local search heuristics of genetic algorithm (GA) and active-set algorithm (ASA), i.e., MWNN-GA-ASA. The detail of each class of the SITR nonlinear COVID-19 system is also discussed. The obtained outcomes of the SITR system are More >