Open Access
ARTICLE
Zengxiang Li1, Yongchong Wu2, Alanoud Al Mazro3, Donghua Jiang4, Jianhua Wu5, Xishun Zhu6,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051762
（This article belongs to the Special Issue: Emerging Technologies in Information Security )
Abstract Hidden capacity, concealment, security, and robustness are essential indicators of hiding algorithms. Currently, hiding algorithms tend to focus on algorithmic capacity, concealment, and security but often overlook the robustness of the algorithms. In practical applications, the container can suffer from damage caused by noise, cropping, and other attacks during transmission, resulting in challenging or even impossible complete recovery of the secret image. An image hiding algorithm based on dynamic region attention in the multi-scale wavelet domain is proposed to address this issue and enhance the robustness of hiding algorithms. In this proposed algorithm, a secret… More >
Open Access
ARTICLE
ByeongYeol An1, JeaHyuk Yang2, Seoyeon Kim2, Taeguen Kim3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052403
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract This paper proposes a new approach to counter cyberattacks using the increasingly diverse malware in cyber security. Traditional signature detection methods that utilize static and dynamic features face limitations due to the continuous evolution and diversity of new malware. Recently, machine learning-based malware detection techniques, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), have gained attention. While these methods demonstrate high performance by leveraging static and dynamic features, they are limited in detecting new malware or variants because they learn based on the characteristics of existing malware. To overcome these limitations, malware… More >
Open Access
ARTICLE
Bingrui Ju1,2, Wenxiang Sun2, Wenzhen Qu1,2,*, Yan Gu2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052159
（This article belongs to the Special Issue: New Trends on Meshless Method and Numerical Analysis)
Abstract In this study, we propose an efficient numerical framework to attain the solution of the extended Fisher-Kolmogorov (EFK) problem. The temporal derivative in the EFK equation is approximated by utilizing the Crank-Nicolson scheme. Following temporal discretization, the generalized finite difference method (GFDM) with supplementary nodes is utilized to address the nonlinear boundary value problems at each time node. These supplementary nodes are distributed along the boundary to match the number of boundary nodes. By incorporating supplementary nodes, the resulting nonlinear algebraic equations can effectively satisfy the governing equation and boundary conditions of the EFK equation. More >
Open Access
ARTICLE
V. G. Saranya*, S. Karthik
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.053825
Abstract Wireless Sensor Networks (WSNs) are a collection of sensor nodes distributed in space and connected through wireless communication. The sensor nodes gather and store data about the real world around them. However, the nodes that are dependent on batteries will ultimately suffer an energy loss with time, which affects the lifetime of the network. This research proposes to achieve its primary goal by reducing energy consumption and increasing the network’s lifetime and stability. The present technique employs the hybrid Mayfly Optimization Algorithm-Enhanced Ant Colony Optimization (MFOA-EACO), where the Mayfly Optimization Algorithm (MFOA) is used to… More >
Open Access
ARTICLE
Khaled Lotfy1,2, A. M. S. Mahdy3,*, Alaa A. El-Bary4, E. S. Elidy1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.053199
Abstract In this research, we focus on the free-surface deformation of a one-dimensional elastic semiconductor medium as a function of magnetic field and moisture diffusivity. The problem aims to analyze the interconnection between plasma and moisture diffusivity processes, as well as thermo-elastic waves. The study examines the photo-thermoelasticity transport process while considering the impact of moisture diffusivity. By employing Laplace’s transformation technique, we derive the governing equations of the photo-thermo-elastic medium. These equations include the equations for carrier density, elastic waves, moisture transport, heat conduction, and constitutive relationships. Mechanical stresses, thermal conditions, and plasma boundary conditions More >
Open Access
ARTICLE
Zhen Wang1, Junsong Xiong1, Shaofan Li2, Xin Lai1,3,*, Xiang Liu3, Lisheng Liu1,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052923
（This article belongs to the Special Issue: Peridynamic Theory and Multi-physical/Multiscale Methods for Complex Material Behavior)
Abstract A fluid-structure interaction approach is proposed in this paper based on Non-Ordinary State-Based Peridynamics (NOSB-PD) and Updated Lagrangian Particle Hydrodynamics (ULPH) to simulate the fluid-structure interaction problem with large geometric deformation and material failure and solve the fluid-structure interaction problem of Newtonian fluid. In the coupled framework, the NOSB-PD theory describes the deformation and fracture of the solid material structure. ULPH is applied to describe the flow of Newtonian fluids due to its advantages in computational accuracy. The framework utilizes the advantages of NOSB-PD theory for solving discontinuous problems and ULPH theory for solving fluid… More >
Open Access
ARTICLE
Lirong Yin1, Lei Wang1, Zhuohang Cai2, Siyu Lu2,*, Ruiyang Wang2, Ahmed AlSanad3, Salman A. AlQahtani3, Xiaobing Chen4, Zhengtong Yin5, Xiaolu Li6, Wenfeng Zheng2,3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052622
（This article belongs to the Special Issue: Emerging Artificial Intelligence Technologies and Applications)
Abstract Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset More >
Open Access
ARTICLE
Chih-Ping Wu*, Ruei-Syuan Chang
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052307
（This article belongs to the Special Issue: Theoretical and Computational Modeling of Advanced Materials and Structures-II)
Abstract This work develops a Hermitian C differential reproducing kernel interpolation meshless (DRKIM) method within the consistent couple stress theory (CCST) framework to study the three-dimensional (3D) microstructure-dependent static flexural behavior of a functionally graded (FG) microplate subjected to mechanical loads and placed under full simple supports. In the formulation, we select the transverse stress and displacement components and their first- and second-order derivatives as primary variables. Then, we set up the differential reproducing conditions (DRCs) to obtain the shape functions of the Hermitian C differential reproducing kernel (DRK) interpolant’s derivatives without using direct differentiation. The interpolant’s… More >
Open Access
ARTICLE
Ibrahim Alameri1,*, Jitka Komarkova2, Tawfik Al-Hadhrami3, Abdulsamad Ebrahim Yahya4, Atef Gharbi5
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052107
（This article belongs to the Special Issue: Computer Modeling for Future Communications and Networks)
Abstract This study is trying to address the critical need for efficient routing in Mobile Ad Hoc Networks (MANETs) from dynamic topologies that pose great challenges because of the mobility of nodes. The main objective was to delve into and refine the application of the Dijkstra's algorithm in this context, a method conventionally esteemed for its efficiency in static networks. Thus, this paper has carried out a comparative theoretical analysis with the Bellman-Ford algorithm, considering adaptation to the dynamic network conditions that are typical for MANETs. This paper has shown through detailed algorithmic analysis that Dijkstra’s… More >
Open Access
ARTICLE
Borja Bordel Sánchez1,*, Ramón Alcarria2, Tomás Robles1
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.050349
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract Future 6G communications are envisioned to enable a large catalogue of pioneering applications. These will range from networked Cyber-Physical Systems to edge computing devices, establishing real-time feedback control loops critical for managing Industry 5.0 deployments, digital agriculture systems, and essential infrastructures. The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised. While full automation will enhance industrial efficiency significantly, it concurrently introduces new cyber risks and vulnerabilities. In particular, unattended systems are highly susceptible to trust issues: malicious nodes and false information can be easily introduced into… More >
Open Access
ARTICLE
Refah Alotaibi1, Sanku Dey2, Ahmed Elshahhat3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.053255
（This article belongs to the Special Issue: Incomplete Data Test, Analysis and Fusion Under Complex Environments)
Abstract A novel inverted generalized gamma (IGG) distribution, proposed for data modelling with an upside-down bathtub hazard rate, is considered. In many real-world practical situations, when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing, censoring strategies are frequently used. From this point of view, in the presence of censored data compiled from the most well-known progressively Type-II censoring technique, this study examines different parameters of the IGG distribution. From a classical point of view, the likelihood and product of spacing estimation methods are… More >
Open Access
REVIEW
Heejae Park1, Tri-Hai Nguyen2, Laihyuk Park1,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052394
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract The emergence of various technologies such as terahertz communications, Reconfigurable Intelligent Surfaces (RIS), and AI-powered communication services will burden network operators with rising infrastructure costs. Recently, the Open Radio Access Network (O-RAN) has been introduced as a solution for growing financial and operational burdens in Beyond 5G (B5G) and 6G networks. O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs. By disaggregating conventional Base Band Units (BBUs) into O-RAN Distributed Units (O-DU) and O-RAN Centralized Units (O-CU), O-RAN offers greater flexibility for upgrades and network automation. However, this openness introduces new security More >
Open Access
ARTICLE
Min-Gyu Kim1, Hwankuk Kim2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051221
（This article belongs to the Special Issue: Advanced Security for Future Mobile Internet: A Key Challenge for the Digital Transformation)
Abstract In the IoT (Internet of Things) domain, the increased use of encryption protocols such as SSL/TLS, VPN (Virtual Private Network), and Tor has led to a rise in attacks leveraging encrypted traffic. While research on anomaly detection using AI (Artificial Intelligence) is actively progressing, the encrypted nature of the data poses challenges for labeling, resulting in data imbalance and biased feature extraction toward specific nodes. This study proposes a reconstruction error-based anomaly detection method using an autoencoder (AE) that utilizes packet metadata excluding specific node information. The proposed method omits biased packet metadata such as… More >
Open Access
ARTICLE
Sonali Das1, Saroja Kumar Rout2, Sujit Kumar Panda1, Pradyumna Kumar Mohapatra3, Abdulaziz S. Almazyad4, Muhammed Basheer Jasser5,6,*, Guojiang Xiong7, Ali Wagdy Mohamed8,9
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051856
（This article belongs to the Special Issue: Advances in Swarm Intelligence Algorithms)
Abstract In blood or bone marrow, leukemia is a form of cancer. A person with leukemia has an expansion of white blood cells (WBCs). It primarily affects children and rarely affects adults. Treatment depends on the type of leukemia and the extent to which cancer has established throughout the body. Identifying leukemia in the initial stage is vital to providing timely patient care. Medical image-analysis-related approaches grant safer, quicker, and less costly solutions while ignoring the difficulties of these invasive processes. It can be simple to generalize Computer vision (CV)-based and image-processing techniques and eradicate human… More >
Open Access
ARTICLE
Amit Singhal1, Krishna Kant Agrawal2, Angeles Quezada3, Adrian Rodriguez Aguiñaga4, Samantha Jiménez4, Satya Prakash Yadav5,,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051363
（This article belongs to the Special Issue: Intelligent Medical Decision Support Systems: Methods and Applications)
Abstract The use of Explainable Artificial Intelligence (XAI) models becomes increasingly important for making decisions in smart healthcare environments. It is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these algorithms. These models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial intelligence. Nevertheless, the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer images. This research presents an advanced investigation of XAI models to classify cancer images. It describes the different levels of explainability… More >
Open Access
ARTICLE
Khushal Das1, Fazeel Abid2, Jawad Rasheed3,4,*, Kamlish5, Tunc Asuroglu6,*, Shtwai Alsubai7, Safeeullah Soomro8
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051335
（This article belongs to the Special Issue: Artificial Intelligence Emerging Trends and Sustainable Applications in Image Processing and Computer Vision)
Abstract Deaf people or people facing hearing issues can communicate using sign language (SL), a visual language. Many works based on rich source language have been proposed; however, the work using poor resource language is still lacking. Unlike other SLs, the visuals of the Urdu Language are different. This study presents a novel approach to translating Urdu sign language (UrSL) using the UrSL-CNN model, a convolutional neural network (CNN) architecture specifically designed for this purpose. Unlike existing works that primarily focus on languages with rich resources, this study addresses the challenge of translating a sign language… More >
Open Access
ARTICLE
Sheng Xiang1, Junhao Ma1, Qunli Shang1, Xianbao Wang1,*, Defu Chen1,2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052759
（This article belongs to the Special Issue: Artificial Intelligence Emerging Trends and Sustainable Applications in Image Processing and Computer Vision)
Abstract Effective small object detection is crucial in various applications including urban intelligent transportation and
pedestrian detection. However, small objects are difficult to detect accurately because they contain less information.
Many current methods, particularly those based on Feature Pyramid Network (FPN), address this challenge by
leveraging multi-scale feature fusion. However, existing FPN-based methods often suffer from inadequate feature
fusion due to varying resolutions across different layers, leading to suboptimal small object detection. To address
this problem, we propose the Two-layer Attention Feature Pyramid Network (TA-FPN), featuring two key modules:
the Two-layer Attention Module (TAM) and the… More >
Graphic Abstract
Open Access
ARTICLE
Shengdong Cheng1, Juncheng Gao1,*, Hongning Qi2,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052830
（This article belongs to the Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications-II)
Abstract Driven piles are used in many geological environments as a practical and convenient structural component. Hence, the determination of the drivability of piles is actually of great importance in complex geotechnical applications. Conventional methods of predicting pile drivability often rely on simplified physical models or empirical formulas, which may lack accuracy or applicability in complex geological conditions. Therefore, this study presents a practical machine learning approach, namely a Random Forest (RF) optimized by Bayesian Optimization (BO) and Particle Swarm Optimization (PSO), which not only enhances prediction accuracy but also better adapts to varying geological environments… More >
Graphic Abstract
Open Access
ARTICLE
Muaadh A. Alsoufi1,*, Maheyzah Md Siraj1, Fuad A. Ghaleb2, Muna Al-Razgan3, Mahfoudh Saeed Al-Asaly3, Taha Alfakih3, Faisal Saeed2
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052112
（This article belongs to the Special Issue: Emerging Technologies in Information Security )
Abstract The rapid growth of Internet of Things (IoT) devices has brought numerous benefits to the interconnected world. However, the ubiquitous nature of IoT networks exposes them to various security threats, including anomaly intrusion attacks. In addition, IoT devices generate a high volume of unstructured data. Traditional intrusion detection systems often struggle to cope with the unique characteristics of IoT networks, such as resource constraints and heterogeneous data sources. Given the unpredictable nature of network technologies and diverse intrusion methods, conventional machine-learning approaches seem to lack efficiency. Across numerous research domains, deep learning techniques have demonstrated… More >
Open Access
ARTICLE
Dijun Rao1,2,3,4, Min Huang1,2,3,5, Xiuzhi Shi4, Zhi Yu6,*, Zhengxiang He7
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051402
（This article belongs to the Special Issue: Bio-inspired Optimization in Engineering and Sciences)
Abstract The denoising of microseismic signals is a prerequisite for subsequent analysis and research. In this research, a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm (BWOA) optimized Variational Mode Decomposition (VMD) joint Wavelet Threshold Denoising (WTD) algorithm (BVW) is proposed. The BVW algorithm integrates VMD and WTD, both of which are optimized by BWOA. Specifically, this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited Intrinsic Mode Functions (BLIMFs). Subsequently, these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold… More >
Open Access
REVIEW
Ebtesam Ahmad Alomari*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.052256
（This article belongs to the Special Issue: Emerging Artificial Intelligence Technologies and Applications)
Abstract As Natural Language Processing (NLP) continues to advance, driven by the emergence of sophisticated large language models such as ChatGPT, there has been a notable growth in research activity. This rapid uptake reflects increasing interest in the field and induces critical inquiries into ChatGPT’s applicability in the NLP domain. This review paper systematically investigates the role of ChatGPT in diverse NLP tasks, including information extraction, Name Entity Recognition (NER), event extraction, relation extraction, Part of Speech (PoS) tagging, text classification, sentiment analysis, emotion recognition and text annotation. The novelty of this work lies in its… More >
Open Access
ARTICLE
Lirong Yin1, Lei Wang1, Siyu Lu2,*, Ruiyang Wang2, Youshuai Yang2, Bo Yang2, Shan Liu2, Ahmed AlSanad3, Salman A. AlQahtani3, Zhengtong Yin4, Xiaolu Li5, Xiaobing Chen6, Wenfeng Zheng3,*
CMES-Computer Modeling in Engineering & Sciences, DOI:10.32604/cmes.2024.051083
Abstract This study addresses the limitations of Transformer models in image feature extraction, particularly their lack of inductive bias for visual structures. Compared to Convolutional Neural Networks (CNNs), the Transformers are more sensitive to different hyperparameters of optimizers, which leads to a lack of stability and slow convergence. To tackle these challenges, we propose the Convolution-based Efficient Transformer Image Feature Extraction Network (CEFormer) as an enhancement of the Transformer architecture. Our model incorporates E-Attention, depthwise separable convolution, and dilated convolution to introduce crucial inductive biases, such as translation invariance, locality, and scale invariance, into the Transformer… More >
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