Shahad Alzahrani¹, Hatim Alsuwat², Emad Alsuwat^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.044718

Abstract Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables. However, the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams. One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks, wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance. In this research paper, we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms. Our framework utilizes latent variables to quantify… More >

Nadeem Salamat¹, Muhammad Kamran^1,2,*, Shahzaib Ashraf¹, Manal Elzain Mohammed Abdulla³, Rashad Ismail³, Mohammed M. Al-Shamiri³

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.044697

Abstract The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy, accessibility, and cost-effectiveness. This paper investigates the potential applications of intuitionistic fuzzy sets (IFS) with rough sets in the context of sparse data. When it comes to capture uncertain information emanating from both upper and lower approximations, these intuitionistic fuzzy rough numbers (IFRNs) are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets, respectively. We use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying properties. We present numerous… More > Graphic Abstract

Rana Muhammad Zulqarnain¹, Wen-Xiu Ma^1,2,3,*, Imran Siddique⁴, Hijaz Ahmad^5,6, Sameh Askar⁷

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.030687

Abstract Green supplier selection is an important debate in green supply chain management (GSCM), attracting global attention from scholars, especially companies and policymakers. Companies frequently search for new ideas and strategies to assist them in realizing sustainable development. Because of the speculative character of human opinions, supplier selection frequently includes unreliable data, and the interval-valued Pythagorean fuzzy soft set (IVPFSS) provides an exceptional capacity to cope with excessive fuzziness, inconsistency, and inexactness through the decision-making procedure. The main goal of this study is to come up with new operational laws for interval-valued Pythagorean fuzzy soft numbers (IVPFSNs) and create two interaction… More >

Dinesh Mavaluru^1,*, Chettupally Anil Carie², Ahmed I. Alutaibi³, Satish Anamalamudi², Bayapa Reddy Narapureddy⁴, Murali Krishna Enduri², Md Ezaz Ahmed¹

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.045277

Abstract In this paper, we present a comprehensive system model for Industrial Internet of Things (IIoT) networks empowered by Non-Orthogonal Multiple Access (NOMA) and Mobile Edge Computing (MEC) technologies. The network comprises essential components such as base stations, edge servers, and numerous IIoT devices characterized by limited energy and computing capacities. The central challenge addressed is the optimization of resource allocation and task distribution while adhering to stringent queueing delay constraints and minimizing overall energy consumption. The system operates in discrete time slots and employs a quasi-static approach, with a specific focus on the complexities of task partitioning and the management… More >

Sharaf Alzoubi¹, Laith Abualigah^{2,3,4,5,6,7,8,*}, Mohamed Sharaf⁹, Mohammad Sh. Daoud¹⁰, Nima Khodadadi¹¹, Heming Jia¹²

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.045170

Abstract This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm (SSOA). The SSOA combines the principles of swarm intelligence and synergistic cooperation to search for optimal solutions efficiently. A synergistic cooperation mechanism is employed, where particles exchange information and learn from each other to improve their search behaviors. This cooperation enhances the exploitation of promising regions in the search space while maintaining exploration capabilities. Furthermore, adaptive mechanisms, such as dynamic parameter adjustment and diversification strategies, are incorporated to balance exploration and exploitation. By leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation, the SSOA… More >

Ahmed Barnawi^1,*, Krishan Kumar², Neeraj Kumar¹, Bander Alzahrani¹, Amal Almansour¹

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.044184

Abstract Landmines continue to pose an ongoing threat in various regions around the world, with countless buried landmines affecting numerous human lives. The detonation of these landmines results in thousands of casualties reported worldwide annually. Therefore, there is a pressing need to employ diverse landmine detection techniques for their removal. One effective approach for landmine detection is UAV (Unmanned Aerial Vehicle) based Airborne Magnetometry, which identifies magnetic anomalies in the local terrestrial magnetic field. It can generate a contour plot or heat map that visually represents the magnetic field strength. Despite the effectiveness of this approach, landmine removal remains a challenging… More >

Duong Q. Nguyen¹, Thinh D. Le³, Phuong D. Nguyen³, Nga T. K. Le², H. Nguyen-Xuan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.043992

Abstract Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications. In this paper, we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network. Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions. To achieve accurate segmentation, we conducted thorough experiments and selected a high-performing model from the trained models. The selected model demonstrates exceptional segmentation performance for complex 3D facial wounds. Furthermore, based on the segmentation model, we propose an improved approach for extracting… More > Graphic Abstract

Yue Xue¹, Dunqiu Fan², Shen Su^1,3,*, Jialu Fu¹, Ning Hu¹, Wenmao Liu², Zhihong Tian^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.031488

Abstract Decentralized finance (DeFi) is a general term for a series of financial products and services. It is based on blockchain technology and has attracted people’s attention because of its open, transparent, and intermediary free. Among them, the DeFi ecosystem based on Ethereum-based blockchains attracts the most attention. However, the current decentralized financial system built on the Ethereum architecture has been exposed to many smart contract vulnerabilities during the last few years. Herein, we believe it is time to improve the understanding of the prevailing Ethereum-based DeFi ecosystem security issues. To that end, we investigate the Ethereum-based DeFi security issues: 1)… More >

Zediao Chen, Feng Liu^*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.046618

Abstract Crack propagation in brittle material is not only crucial for structural safety evaluation, but also has a wideranging impact on material design, damage assessment, resource extraction, and scientific research. A thorough investigation into the behavior of crack propagation contributes to a better understanding and control of the properties of brittle materials, thereby enhancing the reliability and safety of both materials and structures. As an implicit discrete element method, the Discontinuous Deformation Analysis (DDA) has gained significant attention for its developments and applications in recent years. Among these developments, the particle DDA equipped with the bonded particle model is a powerful… More >

Raghunathan Krishankumar¹, Dhruva Sundararajan², K. S. Ravichandran², Edmundas Kazimieras Zavadskas^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.029438

Abstract Hydrogen is the new age alternative energy source to combat energy demand and climate change. Storage of hydrogen is vital for a nation’s growth. Works of literature provide different methods for storing the produced hydrogen, and the rational selection of a viable method is crucial for promoting sustainability and green practices. Typically, hydrogen storage is associated with diverse sustainable and circular economy (SCE) criteria. As a result, the authors consider the situation a multi-criteria decision-making (MCDM) problem. Studies infer that previous models for hydrogen storage method (HSM) selection (i) do not consider preferences in the natural language form; (ii) weights… More >