alexandria engineering journal最新文献

{"title":"AI-enabled routing in next generation networks: A survey","authors":"Fatma Aktas ,&nbsp;Ibraheem Shayea ,&nbsp;Mustafa Ergen ,&nbsp;Bilal Saoud ,&nbsp;Abdulsamad Ebrahim Yahya ,&nbsp;Aldasheva Laura","doi":"10.1016/j.aej.2025.01.095","DOIUrl":"10.1016/j.aej.2025.01.095","url":null,"abstract":"<div><div>Deep learning (DL), a promising and exciting Artificial Intelligence (AI) tool, a potent method to add intelligence to wireless network especially 6 G and satellite networks with complex and dynamic radio situations and also enormous-scale topology. In the face of the characteristics such as heterogeneity, dynamism and time-variability that 6 G and space integrated networks naturally possess, it is difficult for ossified routing algorithms to meet the user's end-to-end OoS and QoE requirements. By analyzing various network arguments like delay, loss rate, and link signal-to-noise ratio, AI techniques have the potential to facilitate the identification of network dynamics such as congestion dots, traffic bottlenecks, and spectrum availability. This study provides a comprehensive survey of how AI algorithms are being utilized for network routing. This survey has three main contributions. Firstly, it represents elaborated tables summarizing the studies and their comparisons. Secondly, it outlines the key findings and missing aspects. Finally, it suggests six specific future research directions. The trend towards intelligence-based routing in next-gen networks has rapidly grown, especially in the last four years. However, to accomplish thorough comparisons and leverage synergies, perform valuable assessments using publicly available datasets and topologies, and execute detailed practical implementations (aligned with up-to-date standards) that can be embraced by industry, considerable effort is required. Reproducible research should be the focus of future efforts rather than new isolated ideas to ensure that these applications are implemented in practice.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 449-474"},"PeriodicalIF":6.2,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143465417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stochastic-based pavement performance and deterioration models: A review of techniques and applications","authors":"Che Shobry Shahid ,&nbsp;Zulhilmi Amir Zainal ,&nbsp;Nur Izzi Md Yusoff ,&nbsp;Noraziah Mohammad ,&nbsp;Zamira Hasanah Zamzuri ,&nbsp;Iswandaru Widyatmoko","doi":"10.1016/j.aej.2025.02.033","DOIUrl":"10.1016/j.aej.2025.02.033","url":null,"abstract":"<div><div>Infrastructure assets, such as pavements, naturally deteriorate over time due to traffic loads, environmental conditions, and other external factors. Traditionally, deterministic models have been employed to predict performance, aiding in work planning and budget allocation. However, these models often fail to capture the complex, non-linear deterioration mechanisms and uncertainties inherent in real-world conditions. Stochastic models provide a more robust and flexible framework by incorporating probabilistic methods to address variability and uncertainty in asset condition data. Techniques such as Markov chains, Semi-Markov processes, Bayesian approaches, and Gaussian Process Regression (GPR) enable more accurate parameter estimation and model selection by integrating all plausible scenarios weighted by their probabilities. These innovated models excel in forecasting future pavement conditions, even with incomplete or uncertain data, and are particularly suited for long-term performance prediction. This paper critically reviews the development and application of stochastic-based degradation models in pavement performance forecasting, highlighting their advantages over deterministic approaches. By accounting for uncertainty and variability, stochastic models not only enhance prediction accuracy but also support cost-effective, data-driven decision-making. They provide infrastructure managers with a reliable foundation for optimizing maintenance strategies, risk assessments, and life cycle cost analyses. Future research should focus on robust calibration techniques, addressing GPR scalability through advanced computational methods, integrating real-time data for dynamic updates, expanding Bayesian uncertainty quantification, and combining deterministic and stochastic models to balance efficiency and accuracy. Incorporating stochastic predictions into life cycle cost analyses will further strengthen decision-support systems for infrastructure management.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 420-437"},"PeriodicalIF":6.2,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional-order modeling of Ebola Virus Disease (EVD) transmission: Insights from infected animals to humans and healthcare deficiencies","authors":"Ali Yousef","doi":"10.1016/j.aej.2025.02.006","DOIUrl":"10.1016/j.aej.2025.02.006","url":null,"abstract":"<div><div>The Ebola virus outbreak in 2014 significantly impacted Guinea, Liberia, and Sierra Leone in Western Africa, with fruit bats serving as natural hosts that transmitted the disease to wild animals. Close contact between infected animals and humans led to a subsequent human-to-human transmission of the virus. In this paper, we develop a fractional-order differential equation model to analyze the spread of Ebola Virus Disease (EVD) through two primary transmission routes: from infected animals to humans (predator-prey dynamics) and human-to-human interactions using an SEIR-based framework. In addition, the model incorporates socio-economic factors, including the lack of healthcare infrastructure, inadequate hospitalization, and low public awareness, which exacerbate virus transmission, particularly during the handling of deceased bodies in traditional burial practices. We apply the Routh-Hurwitz stability criteria to study the local and global stability of the disease-free and endemic equilibrium points, both in the presence and absence of public awareness. Through a Lyapunov function, we demonstrate the global stability of the system’s positive equilibrium. Our numerical simulations reveal that human-to-human transmission, driven by inadequate medical support and insufficient awareness, plays a critical role in the sustained spread of EVD. The findings underscore the importance of improving healthcare systems and enhancing public awareness to control future outbreaks. These results contribute to the understanding of EVD dynamics through a novel fractional-order approach, highlighting critical factors that influence the spread of the disease in resource-limited settings.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 391-408"},"PeriodicalIF":6.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143452978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced network security with an integrated trust-based intrusion detection system for routing protocol","authors":"Ajay Kumar ,&nbsp;Ishan Budhiraja ,&nbsp;Deepak Garg ,&nbsp;Sahil Garg ,&nbsp;Bong Jun Choi ,&nbsp;Mubarak Alrashoud","doi":"10.1016/j.aej.2025.01.087","DOIUrl":"10.1016/j.aej.2025.01.087","url":null,"abstract":"<div><div>The global network called the Internet of Things (IoT) facilitates communication and teamwork by connecting different electronic devices. This combination is especially seen in low-power and non-local networks (LLNs), where equipment is limited to comply with specified standards for connectivity. These systems often use the LLN routing protocol (RPL). However, due to its simplicity, there are many ways to compromise network security. It is also difficult to perform complex operations in the LLN computation due to limited usage. This work presents an advanced design called a Trust-Based RPL Intrusion Detection System (TIDSRPL). TIDSRPL transfers the complex trust to the root node, and TIDSRPL evaluates the node trust based on the network behavior. Depotentialize resources through this strategic shift that preserves energy, storage, and compute resources at the node level. A comparison with the pre-tuned RPL objective function of minimum rank with hysteresis objective function routing protocol low power and non-local (MRHOF-RPL) network shows that TIDSRPL has the best performance in detecting and classifying malware contained in Sinkhole, choosing to submit, and Sybil objecting. More importantly, TIDSRPL achieves a 20%–35% reduction in average packet loss and a 33%–45% improvement in energy efficiency compared to MRHOF-RPL, improving its stability in LLN protection block efficiency.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 378-390"},"PeriodicalIF":6.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical analysis and experimental research on the influence of column structure on the classification performance of hydrocyclone","authors":"Feng Li,&nbsp;Peiyang Li,&nbsp;Yanchao Wang,&nbsp;Dongjin Guo,&nbsp;Huanbo Yang,&nbsp;Hu Han,&nbsp;Ruquan Liang","doi":"10.1016/j.aej.2025.02.030","DOIUrl":"10.1016/j.aej.2025.02.030","url":null,"abstract":"<div><div>A cylinder section serves as a pre-separation area for hydrocyclone classification and a necessary area for fine particles to enter an overflow. Therefore, exploring the influences of cylinder structures on the flow and particle aggregation characteristics inside hydrocyclones is important. In a parabolic cylinder structure, the highest-pressure conversion efficiency was 89.96 %. Experimental comparisons show that the quality efficiency of the parabolic column structure cyclone is 49.56 %, which is 17.63 % higher than that of the conventional feed body, alongside a reduction by 29.70 % of the −20μm particles content in the underflow and an increment by 14.77 % of the −20μm particles content in the overflow, respectively compared to the conventional hydrocyclone.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 271-286"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On quantum trigonometric fractional calculus","authors":"Lakhlifa Sadek ,&nbsp;Ali Algefary","doi":"10.1016/j.aej.2025.02.005","DOIUrl":"10.1016/j.aej.2025.02.005","url":null,"abstract":"<div><div>In this research work, we introduce an innovative concept known as the <span><math><mi>q</mi></math></span>-trigonometric derivative within the framework of the Caputo derivative. Our approach begins by introducing a novel notion of a trigonometric <span><math><mi>q</mi></math></span>-derivative and thoroughly examining its characteristics. We subsequently merge this new definition with the Caputo derivative to introduce a novel approach to <span><math><mi>q</mi></math></span>-fractional calculus. To analytically address this <span><math><mi>q</mi></math></span>-trigonometric system, we effectively employ the <span><math><mi>q</mi></math></span>-Laplace transform to derive solutions. Notably, the bivariate <span><math><mi>q</mi></math></span>-Mittag-Leffler (<span><math><mi>q</mi></math></span>-ML) function plays a significant role in this process. We provide detailed explanations and examples of this approach with two illustrative examples.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 371-377"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prompt-based learning for few-shot class-incremental learning","authors":"Jicheng Yuan ,&nbsp;Hang Chen ,&nbsp;Songsong Tian ,&nbsp;Wenfa Li ,&nbsp;Lusi Li ,&nbsp;Enhao Ning ,&nbsp;Yugui Zhang","doi":"10.1016/j.aej.2025.02.008","DOIUrl":"10.1016/j.aej.2025.02.008","url":null,"abstract":"<div><div>Few-Shot Class-Incremental Learning (FSCIL) aims to enable deep neural networks to incrementally learn new tasks from a limited number of labeled samples, while retaining knowledge of previously learned tasks, mimicking the way humans learn. In this paper, we introduce a novel approach called Prompt Learning for FSCIL (PL-FSCIL), which leverages the power of prompts alongside a pre-trained Vision Transformer (ViT) model to effectively tackle the challenges of FSCIL. Our approach explores the feasibility of directly applying visual prompts in FSCIL, using a simplified model architecture. PL-FSCIL integrates two key prompts: the Domain Prompt and the FSCIL Prompt. Both are tensors incorporated into the attention layer of the ViT network to enhance its capabilities. The Domain Prompt helps the model adapt to new data domains, while the FSCIL Prompt, in combination with a prototype classifier, boosts the model’s ability to handle incremental tasks. We evaluate the performance of PL-FSCIL on well-established benchmark datasets, including CIFAR-100 and CUB-200. The results demonstrate competitive performance, highlighting the method’s promising potential for real-world applications, particularly in scenarios where high-quality labeled data is scarce. The source code is at: <span><span>https://github.com/JichengYuan81/PL-FSCIL</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 287-295"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of truss structures with two archive-boosted MOHO algorithm","authors":"Ghanshyam G. Tejani ,&nbsp;Sunil Kumar Sharma ,&nbsp;Nikunj Mashru ,&nbsp;Pinank Patel ,&nbsp;Pradeep Jangir","doi":"10.1016/j.aej.2025.02.032","DOIUrl":"10.1016/j.aej.2025.02.032","url":null,"abstract":"<div><div>This study identifies the Two-Archive Multi-Objective Hippopotamus Optimization Algorithm (MOHO2Arc) as an advanced multi-objective optimization method for optimizing five widely recognized truss structures. The primary objectives are to minimize the structures' mass and maximum nodal displacement. MOHO2Arc improves upon the standard Multi-Objective Hippopotamus Optimization (MOHO) by incorporating a two-archive strategy, significantly boosting solution diversity and optimization efficiency. A thorough comparative analysis was performed to evaluate the performance of the MOHO2Arc against other established multi-objective optimization algorithms. Performance metrics were applied to assess each algorithm's ability to generate diverse, high-quality solutions. The results demonstrate that MOHO2Arc substantially improves solution diversity and quality. Moreover, statistical analysis using Friedman's test further confirms that MOHO2Arc consistently outperforms the other algorithms in optimization tasks. This research highlights MOHO2Arc as an efficient and promising multi-objective truss structure optimization approach, offering notable advancements over current state-of-the-art techniques.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 296-317"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of social media in shaping visual culture and identity using machine learning methods with featuring engineering","authors":"Qian Yang","doi":"10.1016/j.aej.2025.02.025","DOIUrl":"10.1016/j.aej.2025.02.025","url":null,"abstract":"<div><div>This research investigates the impact of social media in visual culture and identity using three machine learning models which are logistic regression, artificial neural network (ANN), and support vector machine (SVM). Using accuracy, precision, and recall as criteria for categorization, these models were made to analyze the effect of social media on identity formation for individuals and groups with regard to visual cultural trends. The results indicate that the ANN is the best model as it achieved the highest accuracy (0.94), precision (0.91), and recall (0.90), meaning that the model has strong potential to capture the complexity of patterns presenting in visual information as influenced by social media. Contrary, the logistic regression presents the modest performance (accuracy (0.93), precision (0.90), and recall (0.88)) providing reliable insights with interpretability. In contrast, the SVM, registered the least performance (accuracy (0.93), precision (0.87), and recall (0.85)) showing its limitation in pattern deciphering in complex data though such a model still provides advantages in computation efficiency and broader applicability. This research may apply ANN in the analysis of intricate patterns that will describe cultural trends of social media and their impact on visual identity. Such investments in ANN-equipped and well-informed researchers would substantially build the capacity for monitoring.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 349-357"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance enhancement of DRX sleep mode based on signaling/paging traffic arrival in 5G communication systems","authors":"Mustafa M. Sallam,&nbsp;Fayez Wanis Zaki,&nbsp;Mohammed M. Ashour,&nbsp;Hala B. Nafea","doi":"10.1016/j.aej.2025.02.044","DOIUrl":"10.1016/j.aej.2025.02.044","url":null,"abstract":"<div><div>Meeting the demands for faster data rates and minimized latency, one of the significant difficulties facing Millimeter Wave (mmWave) 5 G wireless communication technology is energy consumption. As a result, the battery of the User Equipment (UE) experiences energy absorption. Discontinuous Reception (DRX) sleep mode is activated in the absence of incoming traffic at the Base Station (BS) to prolong the UE battery life and investigate a green communication. To extend the lifespan of the UE battery, the paper presents an enhanced DRX sleep mode. This paper suggests using the DRX mechanism to simultaneously control latency, heat, and energy consumption. Data packets or paging messages are typically the types of traffic that arrive at the BS. Our proposal assesses two system models by considering traffic that enters the UE during its wake-up periods. The Signaling Based DRX is the first system model, and the Enhanced Paging Monitoring (EPM) is the second system model. Both system models rely on the Power Saving Indicator (PSI) and Paging Early Indicator (PEI) as their primary indicators. When compared to the conventional method, these indicators improve power savings, delay, and steady temperature. However, the paper studies different traffic arrival types. The performance assessment of both models involves measuring the power saving factor, average delay and steady temperature of the UE under a uniform rate of data and paging traffic arrivals. The system model and numerical analysis are validated through a MATLAB simulation program. Analytical and computational results are obtained. Power saving factor is increased up to 97 %, average delay is reduced down to 0.1 µsec and steady temperature is reduced to match the normal room temperature of about 27 º C. At the end of this study, the obtained analytical results are compared with some real world measurements related to various international vendors in order to assess relevance and significance. Moreover, impact of the proposal on the maximum throughput is discussed with existence of Line Of Sight (LOS) and None Line Of Sight (NLOS) path loss models appropriate in 5 G communication.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 318-348"},"PeriodicalIF":6.2,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143430163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}