Mohammad Hafiz Mohd Yusof^1,*, Abdullah Mohd Zin², Nurhizam Safie Mohd Satar²

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2445-2466, 2022, DOI:10.32604/cmc.2022.023571 - 29 March 2022

Abstract Due to polymorphic nature of malware attack, a signature-based analysis is no longer sufficient to solve polymorphic and stealth nature of malware attacks. On the other hand, state-of-the-art methods like deep learning require labelled dataset as a target to train a supervised model. This is unlikely to be the case in production network as the dataset is unstructured and has no label. Hence an unsupervised learning is recommended. Behavioral study is one of the techniques to elicit traffic pattern. However, studies have shown that existing behavioral intrusion detection model had a few issues which had… More >

T. G. Sargunam^1,2,*, Lim Way Soong¹, C. M. R. Prabhu¹, Ajay Kumar Singh³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3425-3446, 2022, DOI:10.32604/cmc.2022.023452 - 29 March 2022

Abstract The use of Internet of Things (IoT) applications become dominant in many systems. Its on-chip data processing and computations are also increasing consistently. The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications. The cache memory designed on Static Random-Access Memory (SRAM) cell with features such as low power, high speed, and process tolerance are highly important for the IoT memory system. Therefore, a process tolerant SRAM cell with low power, improved delay and better stability is presented in this research paper. The proposed cell comprises… More >

Mustafa Musa Jaber^1,2,*, Salman Yussof¹, Amer S. Elameer³, Leong Yeng Weng¹, Sura Khalil Abd^2,6, Anand Nayyar^4,5

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2175-2190, 2022, DOI:10.32604/cmc.2022.023387 - 29 March 2022

Abstract Artificial intelligence plays an essential role in the medical and health industries. Deep convolution networks offer valuable services and help create automated systems to perform medical image analysis. However, convolution networks examine medical images effectively; such systems require high computational complexity when recognizing the same disease-affected region. Therefore, an optimized deep convolution network is utilized for analyzing disease-affected regions in this work. Different disease-related medical images are selected and examined pixel by pixel; this analysis uses the gray wolf optimized deep learning network. This method identifies affected pixels by the gray wolf hunting process. The More >

Jyoti Khandelwal¹, Vijay Kumar Sharma¹, Dilbag Singh^2,*, Atef Zaguia³

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3299-3312, 2022, DOI:10.32604/cmc.2022.023116 - 29 March 2022

Abstract Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system. This paper presents an image scrambling method that is very useful for grayscale secret images. In this method, the secret image decomposes in three parts based on the pixel's threshold value. The division of the color image into three parts is very easy based on the color channel but in the grayscale image, it is difficult to implement. The proposed image scrambling method is implemented in image More >

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 - 29 March 2022

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 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 - 29 March 2022

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 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 - 29 March 2022

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 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 - 29 March 2022

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 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 - 29 March 2022

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… 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 - 29 March 2022

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… More >