Monirah Al-Ajlan^*, Mourad Ykhlef

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2053-2076, 2024, DOI:10.32604/cmc.2024.055891 - 18 November 2024

Abstract The ever-growing network traffic threat landscape necessitates adopting accurate and robust intrusion detection systems (IDSs). IDSs have become a research hotspot and have seen remarkable performance improvements. Generative adversarial networks (GANs) have also garnered increasing research interest recently due to their remarkable ability to generate data. This paper investigates the application of (GANs) in (IDS) and explores their current use within this research field. We delve into the adoption of GANs within signature-based, anomaly-based, and hybrid IDSs, focusing on their objectives, methodologies, and advantages. Overall, GANs have been widely employed, mainly focused on solving the More >

Lixiang Wang¹, Longfei Wen^2,3, Rong Tian^2,3,*, Chun Feng^1,4,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011137

Abstract The extended finite element method (XFEM) has been successful in crack analysis but faces challenges in modeling multiple cracks. One challenge is the linear dependence and ill-conditioning of the global stiffness matrix, while another is the geometric description for multiple cracks. To address the first challenge, the Improved XFEM (IXFEM) [1–9] is extended to handle multiple crack problems, effectively eliminating issues of linear dependence and ill-conditioning. Additionally, to overcome the second challenge, a novel level set templated cover cutting method (LSTCCM) [10] is proposed, which combines the advantages of the level set method and cover More >

Zhesheng Zhao¹, Shuai Li¹, Rui Han^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012080

Abstract This study investigates the interactions between droplets and bubbles within water-in-oil (O/W) and oil-in-water (W/O) systems, a fundamental problem of bubble dynamics in binary immiscible fluid systems. Considering the density ratio between the two fluids and the bubble-to-droplet size ratio, we have refined the classical spherical bubble pulsation equation, Rayleigh collapse time, and the natural frequency. In our experimental study, we found that the Rayleigh-Taylor (RT) instability hardly develops on the surface of the droplet when the densities of the two liquids are comparable. This phenomenon is explained using the classic theory of spherical RT More >

Zhanwu Hou¹, Linfeng Xu^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-0, 2024, DOI:10.32604/icces.2024.012892

Abstract The cell-cell interaction between immune cells and tumor cells in the tumor microenvironment plays an important role in the genesis and development of tumors. However, due to the lack of methods to systematically identify the interaction between the two, the specific molecular mechanisms involved are not well understood. The microfluidic platform provides a high-throughput and precise method for studying cell interactions in microreactive systems. However, the traditional platform for studying cell interactions is the closed droplet system, which is easy to cause the consumption of nutrients and the accumulation of wastes, thus interfering with cell… More >

Brij B. Gupta^1,2,3,4,*, Akshat Gaurav⁵, Varsha Arya^6,7, Razaz Waheeb Attar⁸, Shavi Bansal⁹, Ahmed Alhomoud¹⁰, Kwok Tai Chui¹¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2165-2183, 2024, DOI:10.32604/cmes.2024.056473 - 31 October 2024

Abstract Phishing attacks present a serious threat to enterprise systems, requiring advanced detection techniques to protect sensitive data. This study introduces a phishing email detection framework that combines Bidirectional Encoder Representations from Transformers (BERT) for feature extraction and CNN for classification, specifically designed for enterprise information systems. BERT’s linguistic capabilities are used to extract key features from email content, which are then processed by a convolutional neural network (CNN) model optimized for phishing detection. Achieving an accuracy of 97.5%, our proposed model demonstrates strong proficiency in identifying phishing emails. This approach represents a significant advancement in More >

Attiya Khan¹, Muhammad Rizwan², Ovidiu Bagdasar^2,3, Abdulatif Alabdulatif^4,*, Sulaiman Alamro⁴, Abdullah Alnajim⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2121-2141, 2024, DOI:10.32604/cmes.2024.054380 - 31 October 2024

Abstract The Internet of Medical Things (IoMT) is an emerging technology that combines the Internet of Things (IoT) into the healthcare sector, which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs. As IoMT devices become more scalable, Smart Healthcare Systems (SHS) have become increasingly vulnerable to cyberattacks. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security. An IDS monitors systems or networks for suspicious activities or potential threats, safeguarding internal networks. This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets. We propose More >

Alaa U. Khawaja¹, Ahmad Shaf^2,*, Faisal Al Thobiani³, Tariq Ali⁴, Muhammad Irfan⁵, Aqib Rehman Pirzada², Unza Shahkeel²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2399-2420, 2024, DOI:10.32604/cmes.2024.054257 - 31 October 2024

Abstract Electric motor-driven systems are core components across industries, yet they’re susceptible to bearing faults. Manual fault diagnosis poses safety risks and economic instability, necessitating an automated approach. This study proposes FTCNNLSTM (Fine-Tuned TabNet Convolutional Neural Network Long Short-Term Memory), an algorithm combining Convolutional Neural Networks, Long Short-Term Memory Networks, and Attentive Interpretable Tabular Learning. The model preprocesses the CWRU (Case Western Reserve University) bearing dataset using segmentation, normalization, feature scaling, and label encoding. Its architecture comprises multiple 1D Convolutional layers, batch normalization, max-pooling, and LSTM blocks with dropout, followed by batch normalization, dense layers, and More >

Enas Yahya Alqulaity¹, Wael M.S. Yafooz^1,*, Abdullah Alourani², Ayman Jaradat³

Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 907-928, 2024, DOI:10.32604/iasc.2024.055470 - 31 October 2024

Abstract Arabic dialect identification is essential in Natural Language Processing (NLP) and forms a critical component of applications such as machine translation, sentiment analysis, and cross-language text generation. The difficulties in differentiating between Arabic dialects have garnered more attention in the last 10 years, particularly in social media. These difficulties result from the overlapping vocabulary of the dialects, the fluidity of online language use, and the difficulties in telling apart dialects that are closely related. Managing dialects with limited resources and adjusting to the ever-changing linguistic trends on social media platforms present additional challenges. A strong… More >

Shahlaa Mashhadani^1,*, Wisal Hashim Abdulsalam¹, Oday Ali Hassen², Saad M. Darwish³

Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 805-828, 2024, DOI:10.32604/iasc.2024.054611 - 31 October 2024

Abstract Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also… More >

Eric Bourreau¹, Gérard Fleury², Philippe Lacomme^2,*

Journal of Quantum Computing, Vol.6, pp. 25-51, 2024, DOI:10.32604/jqc.2024.048792 - 25 October 2024

Abstract The paper presents a novel quantum method for addressing two fundamental routing problems: the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), both central to routing challenges. The proposed method, named the Indirect Quantum Approximate Optimization Algorithm (IQAOA), leverages an indirect solution representation using ranking. Our contribution focuses on two main areas: 1) the indirect representation of solutions, and 2) the integration of this representation into an extended version of QAOA, called IQAOA. This approach offers an alternative to QAOA and includes the following components: 1) a quantum parameterized circuit designed to simulate… More >