Ming Cheng¹, Shiming Li^1,3,*, Yuhe Wang¹, Guohui Zhou¹, Peng Han¹, Yan Zhao²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427

Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the projection covariance matrix adaptive evolution… More >

Ali Arshad^1,*, Muhammad Nadeem², Saman Riaz¹, Syeda Wajiha Zahra², Ashit Kumar Dutta³, Zaid Alzaid⁴, Rana Alabdan⁵, Badr Almutairi⁶, Sultan Almotairi^4,7

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3065-3089, 2023, DOI:10.32604/cmc.2023.035695

Abstract There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data, but these techniques and algorithms cannot be used to protect data from an attacker. Cloud cryptography is the best way to transmit data in a secure and reliable format. Various researchers have developed various mechanisms to transfer data securely, which can convert data from readable to unreadable, but these algorithms are not sufficient to provide complete data security. Each algorithm has some data security issues. If some effective data protection techniques are used, the attacker will not be able to… More >

Fawad Nasim^1,2,*, Muhammad Adnan Yousaf¹, Sohail Masood^1,2, Arfan Jaffar^1,2, Muhammad Rashid³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2865-2877, 2023, DOI:10.32604/iasc.2023.034258

Abstract Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We proposed a data-driven probabilistic system… More >

AAYUSHI RANDHAWA^1,2, SAYAN DEB DUTTA¹, KEYA GANGULY¹, TEJAL V. PATIL^1,2, RACHMI LUTHFIKASARI¹, KI-TAEK LIM^1,2,*

BIOCELL, Vol.47, No.4, pp. 789-808, 2023, DOI:10.32604/biocell.2023.026217

Abstract Tissues are made up of cells and the extracellular matrix (ECM) which surrounds them. These cells and tissues are actively adaptable to enduring significant stress that occurs in daily life. This astonishing mechanical stress develops due to the interaction between the live cells and the non-living ECM. Cells in the matrix microenvironment can sense the signals and forces produced and initiate a signaling cascade that plays a crucial role in the body’s normal functioning and influences various properties of the native cells, including growth, proliferation, and differentiation. However, the matrix’s characteristic features also impact the repair and regeneration of the… More >

Mohamed Maher Ata¹, Reem N. Yousef², Faten Khalid Karim^3,*, Doaa Sami Khafaga³

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1597-1616, 2023, DOI:10.32604/csse.2023.034375

Abstract Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the… More >

Hiam Alquran^1,2, Yazan Al-Issa³, Mohammed Alslatie⁴, Isam Abu-Qasmieh¹, Amin Alqudah³, Wan Azani Mustafa^5,7,*, Yasmin Mohd Yacob^6,7

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861

Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance of 3D features and 2D… More >

Mohammad Aslefallah¹, Şuayip Yüzbaşi², Saeid Abbasbandy^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1687-1706, 2023, DOI:10.32604/cmes.2023.025647

Abstract In this work, the exponential approximation is used for the numerical simulation of a nonlinear SITR model as a system of differential equations that shows the dynamics of the new coronavirus (COVID-19). The SITR mathematical model is divided into four classes using fractal parameters for COVID-19 dynamics, namely, susceptible (S), infected (I), treatment (T), and recovered (R). The main idea of the presented method is based on the matrix representations of the exponential functions and their derivatives using collocation points. To indicate the usefulness of this method, we employ it in some cases. For error analysis of the method, the… More > Graphic Abstract

Xiaojie Zhao¹, Xiankui Meng¹, Ruyong Ren², Shaozhang Niu^2,*, Zhenguang Gao³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1765-1781, 2023, DOI:10.32604/cmc.2023.029552

Abstract Detecting double Joint Photographic Experts Group (JPEG) compression for color images is vital in the field of image forensics. In previous researches, there have been various approaches to detecting double JPEG compression with different quantization matrices. However, the detection of double JPEG color images with the same quantization matrix is still a challenging task. An effective detection approach to extract features is proposed in this paper by combining traditional analysis with Convolutional Neural Networks (CNN). On the one hand, the number of nonzero pixels and the sum of pixel values of color space conversion error are provided with 12-dimensional features… More >

Xiang Zhang¹, Xiaona Zhang^2,4,*, Xiaorui Zhang^3,5,6, Wei Sun^6,7, Ruohan Meng⁸, Xingming Sun¹

Computer Systems Science and Engineering, Vol.46, No.1, pp. 225-239, 2023, DOI:10.32604/csse.2023.034915

Abstract The data in the blockchain cannot be tampered with and the users are anonymous, which enables the blockchain to be a natural carrier for covert communication. However, the existing methods of covert communication in blockchain suffer from the predefined channel structure, the capacity of a single transaction is not high, and the fixed transaction behaviors will lower the concealment of the communication channel. Therefore, this paper proposes a derivation matrix-based covert communication method in blockchain. It uses dual-key to derive two types of blockchain addresses and then constructs an address matrix by dividing addresses into multiple layers to make full… More >

Chong Wang¹, Tongxing Zuo^1,2, Haitao Han^1,2, Qianglong Wang^1,2, Han Zhang¹, Zhenyu Liu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 655-683, 2023, DOI:10.32604/cmes.2023.025153

Abstract This paper presents an extended sequential element rejection and admission (SERA) topology optimization method with a region partitioning strategy. Based on the partitioning of a design domain into solid regions and weak regions, the proposed optimization method sequentially implements finite element analysis (FEA) in these regions. After standard FEA in the solid regions, the boundary displacement of the weak regions is constrained using the numerical solution of the solid regions as Dirichlet boundary conditions. This treatment can alleviate the negative effect of the material interpolation model of the topology optimization method in the weak regions, such as the condition number… More > Graphic Abstract