Xiaoyan Su^1,*, Shuwen Shang¹, Zhihui Xu², Hong Qian¹, Xiaolei Pan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957

Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs in SPAR-H based on the… More > Graphic Abstract

Jebran Khan¹, Kashif Ahmad², Kyung-Ah Sohn^1,3,*

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2869-2894, 2023, DOI:10.32604/csse.2023.040159

Abstract In recent years, the growing popularity of social media platforms has led to several interesting natural language processing (NLP) applications. However, these social media-based NLP applications are subject to different types of adversarial attacks due to the vulnerabilities of machine learning (ML) and NLP techniques. This work presents a new low-level adversarial attack recipe inspired by textual variations in online social media communication. These variations are generated to convey the message using out-of-vocabulary words based on visual and phonetic similarities of characters and words in the shortest possible form. The intuition of the proposed scheme is to generate adversarial examples… More >

M. A. P. Manimekalai¹, M. Karthikeyan¹, I. Thusnavis Bella Mary¹, K. Martin Sagayam¹, Ahmed A Elngar², Unai Fernandez-Gamiz³, Hatıra Günerhan^4,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1325-1353, 2023, DOI:10.32604/cmc.2023.035856

Abstract This paper proposes a cryptographic technique on images based on the Sudoku solution. Sudoku is a number puzzle, which needs applying defined protocols and filling the empty boxes with numbers. Given a small size of numbers as input, solving the sudoku puzzle yields an expanded big size of numbers, which can be used as a key for the Encryption/Decryption of images. In this way, the given small size of numbers can be stored as the prime key, which means the key is compact. A prime key clue in the sudoku puzzle always leads to only one solution, which means the… More >

Mohammed Aly^1,*, Abdullah Shawan Alotaibi²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 557-582, 2023, DOI:10.32604/cmc.2023.042493

Abstract Tumor segmentation is a valuable tool for gaining insights into tumors and improving treatment outcomes. Manual segmentation is crucial but time-consuming. Deep learning methods have emerged as key players in automating brain tumor segmentation. In this paper, we propose an efficient modified U-Net architecture, called EMU-Net, which is applied to the BraTS 2020 dataset. Our approach is organized into two distinct phases: classification and segmentation. In this study, our proposed approach encompasses the utilization of the gray-level co-occurrence matrix (GLCM) as the feature extraction algorithm, convolutional neural networks (CNNs) as the classification algorithm, and the chi-square method for feature selection.… More >

Sidra Abbas¹, Gabriel Avelino Sampedro^2,3, Shtwai Alsubai⁴, Ahmad Almadhor⁵, Tai-hoon Kim^6,*

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 665-680, 2023, DOI:10.32604/cmc.2023.041031

Abstract Cardiac disease is a chronic condition that impairs the heart’s functionality. It includes conditions such as coronary artery disease, heart failure, arrhythmias, and valvular heart disease. These conditions can lead to serious complications and even be life-threatening if not detected and managed in time. Researchers have utilized Machine Learning (ML) and Deep Learning (DL) to identify heart abnormalities swiftly and consistently. Various approaches have been applied to predict and treat heart disease utilizing ML and DL. This paper proposes a Machine and Deep Learning-based Stacked Model (MDLSM) to predict heart disease accurately. ML approaches such as eXtreme Gradient Boosting (XGB),… More >

Aaqib Inam¹, Zhu Li^1,*, Salah-ud-din Khokhar², Zubia Zafar³, Muhammad Imran⁴

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 699-715, 2023, DOI:10.32604/cmc.2023.039707

Abstract Mosquitoes are of great concern for occasionally carrying noxious diseases (dengue, malaria, zika, and yellow fever). To control mosquitoes, it is very crucial to effectively monitor their behavioral trends and presence. Traditional mosquito repellent works by heating small pads soaked in repellant, which then diffuses a protected area around you, a great alternative to spraying yourself with insecticide. But they have limitations, including the range, turning them on manually, and then waiting for the protection to kick in when the mosquitoes may find you. This research aims to design a fuzzy-based controller to solve the above issues by automatically determining… More >

Qingyun Zeng^1,2, Mingxin Zheng^1,*, Dan Huang²

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.12, pp. 2981-3005, 2023, DOI:10.32604/fdmp.2023.029427

Abstract A complex interface exists between water flow and solid particles during hydraulic soil erosion. In this study, the particle discrete element method (DEM) has been used to simulate the hydraulic erosion of a granular soil under moving bed conditions and surrounding terrain changes. Moreover, the weakly compressible smoothed particle hydrodynamics (WCSPH) approach has been exploited to simulate the instability process of the free surface fluid and its propagation characteristics at the solid–liquid interface. The influence of a suspended medium on the water flow dynamics has been characterized using the mixed viscosity concept accounting for the solid–liquid mixed particle volume ratio.… More > Graphic Abstract

Peng Liu¹, Qian He^1,*, Baokang Zhao², Biao Guo¹, Zhongyi Zhai¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3325-3343, 2023, DOI:10.32604/cmc.2023.041167

Abstract Cloud storage and edge computing are utilized to address the storage and computational challenges arising from the exponential data growth in IoT. However, data privacy is potentially risky when data is outsourced to cloud servers or edge services. While data encryption ensures data confidentiality, it can impede data sharing and retrieval. Attribute-based searchable encryption (ABSE) is proposed as an effective technique for enhancing data security and privacy. Nevertheless, ABSE has its limitations, such as single attribute authorization failure, privacy leakage during the search process, and high decryption overhead. This paper presents a novel approach called the blockchain-assisted efficient multi-authority attribute-based… More >

Abdulgbar A. R. Farea¹, Gehad Abdullah Amran^2,*, Ebraheem Farea³, Amerah Alabrah^4,*, Ahmed A. Abdulraheem⁵, Muhammad Mursil⁶, Mohammed A. A. Al-qaness⁷

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3605-3622, 2023, DOI:10.32604/cmc.2023.040121

Abstract E-commerce, online ticketing, online banking, and other web-based applications that handle sensitive data, such as passwords, payment information, and financial information, are widely used. Various web developers may have varying levels of understanding when it comes to securing an online application. Structured Query language SQL injection and cross-site scripting are the two vulnerabilities defined by the Open Web Application Security Project (OWASP) for its 2017 Top Ten List Cross Site Scripting (XSS). An attacker can exploit these two flaws and launch malicious web-based actions as a result of these flaws. Many published articles focused on these attacks’ binary classification. This… More >

Tianzhe Jiao, Xiaoyue Feng, Chaopeng Guo, Dongqi Wang, Jie Song^*

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3585-3603, 2023, DOI:10.32604/cmc.2023.040068

Abstract Mobile-edge computing (MEC) is a promising technology for the fifth-generation (5G) and sixth-generation (6G) architectures, which provides resourceful computing capabilities for Internet of Things (IoT) devices, such as virtual reality, mobile devices, and smart cities. In general, these IoT applications always bring higher energy consumption than traditional applications, which are usually energy-constrained. To provide persistent energy, many references have studied the offloading problem to save energy consumption. However, the dynamic environment dramatically increases the optimization difficulty of the offloading decision. In this paper, we aim to minimize the energy consumption of the entire MEC system under the latency constraint by… More >