B. Priestly Shan¹, O. Jeba Shiney¹, Sharzeel Saleem², V. Rajinikanth³, Atef Zaguia⁴, Dilbag Singh^5,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2749-2763, 2022, DOI:10.32604/cmc.2022.023057

Abstract Low contrast of Magnetic Resonance (MR) images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated diagnosis. State-of-the-art contrast boosting techniques intolerably alter inherent features of MR images. Drastic changes in brightness features, induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic meanings. To overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as well. This method termed as Power-law and Logarithmic Modification-based Histogram Equalization (PLMHE) partitions the histogram of the image into two… More >

Anil Kumar Yadav¹, R. K. Pateriya², Nirmal Kumar Gupta³, Punit Gupta^4,*, Dinesh Kumar Saini⁴, Mohammad Alahmadi⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052

Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN. PCA-SVM, however,… More >

Ibrahim M. Mehedi^1,2,*, Abdulah Jeza Aljohani^1,2, Md Mottahir Alam¹, Mohamed Mahmoud³, Mohammed J. Abdulaal¹, Muhammad Bilal^1,2, Waleed Alasmary⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2341-2355, 2022, DOI:10.32604/cmc.2022.022993

Abstract The Ball and beam system (BBS) is an attractive laboratory experimental tool because of its inherent nonlinear and open-loop unstable properties. Designing an effective ball and beam system controller is a real challenge for researchers and engineers. In this paper, the control design technique is investigated by using Intelligent Dynamic Inversion (IDI) method for this nonlinear and unstable system. The proposed control law is an enhanced version of conventional Dynamic Inversion control incorporating an intelligent control element in it. The Moore-Penrose Generalized Inverse (MPGI) is used to invert the prescribed constraint dynamics to realize the baseline control law. A sliding… More >

Salman Khan¹, Mukhtaj Khan^1,2, Nadeem Iqbal¹, Mohd Amiruddin Abd Rahman^3,*, Muhammad Khalis Abdul Karim³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2243-2258, 2022, DOI:10.32604/cmc.2022.022901

Abstract Piwi-interacting Ribonucleic acids (piRNAs) molecule is a well-known subclass of small non-coding RNA molecules that are mainly responsible for maintaining genome integrity, regulating gene expression, and germline stem cell maintenance by suppressing transposon elements. The piRNAs molecule can be used for the diagnosis of multiple tumor types and drug development. Due to the vital roles of the piRNA in computational biology, the identification of piRNAs has become an important area of research in computational biology. This paper proposes a two-layer predictor to improve the prediction of piRNAs and their function using deep learning methods. The proposed model applies various feature… More >

Seung-Yeon Hwang¹, Jeong-Joon Kim^2,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2649-2663, 2022, DOI:10.32604/cmc.2022.022593

Abstract Artificial intelligence, which has recently emerged with the rapid development of information technology, is drawing attention as a tool for solving various problems demanded by society and industry. In particular, convolutional neural networks (CNNs), a type of deep learning technology, are highlighted in computer vision fields, such as image classification and recognition and object tracking. Training these CNN models requires a large amount of data, and a lack of data can lead to performance degradation problems due to overfitting. As CNN architecture development and optimization studies become active, ensemble techniques have emerged to perform image classification by combining features extracted… More >

Muhammad Sanaullah^1,*, Muhammad Kashif², Babar Ahmad², Tauqeer Safdar², Mehdi Hassan³, Mohd Hilmi Hasan⁴, Amir Haider⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2501-2519, 2022, DOI:10.32604/cmc.2022.021990

Abstract Communication is a basic need of every human being to exchange thoughts and interact with the society. Acute peoples usually confab through different spoken languages, whereas deaf people cannot do so. Therefore, the Sign Language (SL) is the communication medium of such people for their conversation and interaction with the society. The SL is expressed in terms of specific gesture for every word and a gesture is consisted in a sequence of performed signs. The acute people normally observe these signs to understand the difference between single and multiple gestures for singular and plural words respectively. The signs for singular… More >

R. Anitha^*, B. Vijayalakshmi

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3447-3463, 2022, DOI:10.32604/cmc.2022.021519

Abstract In the current scenario, data transmission over the network is a challenging task as there is a need for protecting sensitive data. Traditional encryption schemes are less sensitive and less complex thus prone to attacks during transmission. It has been observed that an encryption scheme using chaotic theory is more promising due to its non-linear and unpredictable behavior. Hence, proposed a novel hybrid image encryption scheme with multi-scroll attractors and quantum chaos logistic maps (MSA-QCLM). The image data is classified as inter-bits and intra-bits which are permutated separately using multi scroll attractor & quantum logistic maps to generate random keys.… More >

T. Khatir^1,2, M. Bouchetara², K. Derrar², M. Djafri³, S. Khatir⁴, M. Abdel Wahab^5,6,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2259-2273, 2022, DOI:10.32604/cmc.2022.020879

Abstract Braking efficiency is characterized by reduced braking time and distance, and therefore passenger safety depends on the design of the braking system. During the braking of a vehicle, the braking system must dissipate the kinetic energy by transforming it into heat energy. A too high temperature can lead to an almost total loss of braking efficiency. An excessive rise in brake temperature can also cause surface cracks extending to the outside edge of the drum friction surface. Heat transfer and temperature gradient, not to forget the vehicle's travel environment (high speed, heavy load, and steeply sloping road conditions), must thus… More >

Rihem Farkh^1,2, Saad Alhuwaimel^3,*, Sultan Alzahrani³, Khaled Al Jaloud¹, Mohammad Tabrez Quasim⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2811-2824, 2022, DOI:10.32604/cmc.2022.020259

Abstract Several applications of machine learning and artificial intelligence, have acquired importance and come to the fore as a result of recent advances and improvements in these approaches. Autonomous cars are one such application. This is expected to have a significant and revolutionary influence on society. Integration with smart cities, new infrastructure and urban planning with sophisticated cyber-security are some of the current ramifications of self-driving automobiles. The autonomous automobile, often known as self-driving systems or driverless vehicles, is a vehicle that can perceive its surroundings and navigate predetermined routes without human involvement. Cars are on the verge of evolving into… More >

Naglaa F. Soliman^1,2, E. A. Alabdulkreem³, Abeer D. Algarni^1,*, Ghada M. El Banby⁴, Fathi E. Abd El-Samie^1,5, Ahmed Sedik⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2545-2563, 2022, DOI:10.32604/cmc.2022.020107

Abstract For military warfare purposes, it is necessary to identify the type of a certain weapon through video stream tracking based on infrared (IR) video frames. Computer vision is a visual search trend that is used to identify objects in images or video frames. For military applications, drones take a main role in surveillance tasks, but they cannot be confident for long-time missions. So, there is a need for such a system, which provides a continuous surveillance task to support the drone mission. Such a system can be called a Hybrid Surveillance System (HSS). This system is based on a distributed… More >