alexandria engineering journal最新文献

{"title":"AI as the new fourth “P” of marketing: A statistical and machine learning modelling approach to marketing performance","authors":"Badrea Al Oraini","doi":"10.1016/j.aej.2026.01.045","DOIUrl":"10.1016/j.aej.2026.01.045","url":null,"abstract":"<div><div>This paper undertakes a statistical and machine learning modelling analysis to explore how Artificial Intelligence works as a new ‘fourth P’ for marketing and how it alters the classical formula for a data-driven process. This paper uses a mathematical statistical method to analyse business-level data from 281 companies in Saudi Arabia. This research draws upon theories such as Resource-Based View, Dynamic Capability Theory, and TOE framework. Through correlation analysis, regression analysis, and mediation analysis conducted using Random Forest analysis, Gradient Boosting analysis, and Artificial Neural Network (ANN) analysis, the impact of AI on marketing performance as a function of product innovation, pricing accuracy, channel flexibility, and promotional personalization was objectively quantified. The findings revealed a robust correlation between the implementation of AI and marketing performance (β = 0.842, R-squared = 0.72, p &lt; 0.001), and good predictability of marketing performance using machine learning analysis (R-squared ANN analysis = 0.94). The SHAP evaluation disclosed that the factor of promotional personalization has the highest influence on marketing performance. The findings effectively verify that AI functions as a strategic and measurable integrator of the marketing mix. Through a strategic integration of mathematical findings and strategic marketing principles, AI is positioned as the new fourth ‘P’ of marketing.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"139 ","pages":"Pages 126-138"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147403386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biobutanol and carotenoid production from Hindakia tetrachotoma grown in microplastic-contaminated wastewater within a biorefinery concept","authors":"Melih Onay","doi":"10.1016/j.aej.2026.02.018","DOIUrl":"10.1016/j.aej.2026.02.018","url":null,"abstract":"<div><div>Microalgae can produce pigments and biofuels together within the biorefinery concept. The aim of this study was to produce carotenoids and biobutanol from <em>H. tetrachotoma</em> grown in wastewater contaminated with microplastics such as polypropylene (PP) and polyethylene (PE). In this study, <em>H. tetrachotoma</em> was grown under blue, white and red light to determine the maximum biomass and carbohydrate productivities and in various amounts of PP and PE (25, 75, and 150 mg/L) along with two mixtures of microalgae (25, 75, and 150 mg/L PP+PE) to examine how they affect carotenoids and biobutanol. The highest biobutanol productivity and carotenoid content were 0.040 ± 0.001 g/g biomass and 4.6 ± 0.1 mg/g biomass at 75 mg/L of PP+PE, respectively. This resulted in an increase of approximately 66 % for biobutanol. Also, to show the stress effects of microplastics on microalgae, CAT, SOD, MDA and APX activities were examined and the highest CAT, SOD, APX enzyme activities were 87 ± 3 U/mg protein, 108 ± 4 U/mg protein and 14.2 ± 0.3 U/mg protein at 75 mg/L of PP+PE, respectively. In conclusion, <em>H. tetrachotoma</em> can be used for both carotenoid and biobutanol production in the light of the biorefinery concept in wastewater contaminated with microplastics.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"139 ","pages":"Pages 84-97"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147403387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of hydrogen blending on flow assurance assessment in subsea natural gas pipelines","authors":"Ahmed S.A. Soliman Ahmed Soliman ,&nbsp;Mohamed A. Kotb Mohamed Kotb ,&nbsp;Adel A. Banawan Adel Banawan","doi":"10.1016/j.aej.2026.02.012","DOIUrl":"10.1016/j.aej.2026.02.012","url":null,"abstract":"<div><div>Hydrogen blending into offshore natural gas pipelines is increasingly regarded as a transitional decarbonization pathway; however, its implications for deep-water subsea flow assurance remain insufficiently understood. This study presents a field-validated assessment of hydrogen–natural gas co-transport in a deep-water subsea pipeline, integrating hydraulic, thermal, corrosion, erosion, hydrate, vapor-fraction, and heat-transfer analyses within a unified modeling framework. The Atoll gas field (Eastern Mediterranean, approximately 920 m water depth) is selected as a representative case study. A 20-inch subsea production and export pipeline system is simulated using Aspen HYSYS® Version 14 and validated against High Integrity Pipeline Protection System (HIPPS) field data, with deviations below 3 %. Hydrogen blending levels ranging from 0 to 50 vol% are investigated. The results indicate that hydrogen enrichment reduces overall pressure losses and enhances vapor-phase stability due to lower mixture density, while increasing flow velocity and erosion-related parameters within acceptable operational limits. Accelerated cooling associated with hydrogen’s higher thermal conductivity increases operational hydrate risk, governed primarily by thermo-hydraulic effects rather than hydrate thermodynamics. A 50 % hydrogen blend is adopted as a conservative upper-bound scenario to examine limiting flow assurance behavior. Overall, the findings provide practical insights for offshore hydrogen blending feasibility and preliminary flow assurance screening.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"139 ","pages":"Pages 31-44"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147403719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An intelligent essay scoring system based on a BERT-driven Deep Self-Supervised Contrastive Learning Network","authors":"Junqiao Wang ,&nbsp;Lu Luo","doi":"10.1016/j.aej.2026.02.016","DOIUrl":"10.1016/j.aej.2026.02.016","url":null,"abstract":"<div><div>Automated essay scoring is of great practical value in educational applications, yet existing methods heavily rely on labeled data and insufficiently distinguish semantic differences across score levels. To address these issues, we propose a BERT (Bidirectional Encoder Representation from Transformers) based Deep Self-Supervised Contrastive Learning Network (D2SCLN). The model employs BERT and a Transformer encoder to learn document-level representations, optimized via supervised classification. To better exploit unlabeled data, a self-supervised reconstruction mechanism is introduced to enhance representation robustness. In addition, supervised contrastive learning is incorporated to improve discrimination among different scoring levels. Experiments on the ASAP dataset show that D2SCLN consistently outperforms representative baselines under multiple data splits in terms of Accuracy, AUC, and AUPR, demonstrating its effectiveness and stability.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"140 ","pages":"Pages 1-9"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147411567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Power grid security situation awareness and adaptive grayscale classification method based on transformer architecture","authors":"Mingfei Zeng,&nbsp;Hushuang Zeng","doi":"10.1016/j.aej.2026.02.014","DOIUrl":"10.1016/j.aej.2026.02.014","url":null,"abstract":"<div><div>In this study, we address the evolving cybersecurity threats facing modern power grids. Existing approaches often rely on discrete label–based classification and single-modality analysis, which fail to capture the continuous nature of threat intensity and the heterogeneity of power grid data. To overcome these limitations, we propose PGTSAGA (Power Grid Transformer for Security Situational Awareness and Adaptive Grayscale Assessment), a novel Transformer-based framework for multimodal power grid security analysis. PGTSAGA integrates SCADA measurements, PMU synchrophasor data, and network traffic data through a Trimodal Cross-Attention Mechanism, enabling effective multimodal feature fusion. A Hierarchical Transformer Architecture extracts threat features across multiple temporal and relational scales, from local anomalies to global grid conditions. Furthermore, a Continuous Threat Evaluator based on variational inference models threat intensity as a probability distribution, capturing uncertainty in noisy data. Complementing this, an Adaptive Grayscale Classification method grounded in fuzzy set theory dynamically maps threat levels into a continuous grayscale space, reducing errors caused by hard discrete classification. Experiments on real-world datasets demonstrate that, compared with Crossformer, PGTSAGA achieves a 5.4 % relative improvement in Accuracy, approximately 6 % increases in Precision, Recall, and F1, a 4.12 % increase in AUC, and a 40.74 % relative reduction in the false alarm rate.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"140 ","pages":"Pages 110-123"},"PeriodicalIF":6.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147411564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of simulation parameters on bulk carrier resistance: A comparative analysis of computational and experimental fluid dynamics (CFD/EFD)","authors":"Khaled A. Hafez ,&nbsp;Ahmed T. Ahmed ,&nbsp;Mohamed M. Helal","doi":"10.1016/j.aej.2026.01.036","DOIUrl":"10.1016/j.aej.2026.01.036","url":null,"abstract":"<div><div>This research evaluates the computational resource requirements for CFD simulation parameters in predicting ship resistance, using the <strong><u>V</u></strong>olume <strong><u>o</u></strong>f <strong><u>F</u></strong>luid (VOF) method with the ISIS-CFD solver on a scaled 57,000-ton deadweight (DWT), single-screw bulk carrier, Oceanbeauty. The paper explores the effects of various simulation parameters such as the non-dimensional distance to the wall of the nearest cell center (y⁺), near wall treatment, turbulence model, time step (<span><math><mrow><mi>Δ</mi><mi>t</mi></mrow></math></span>), and discretization scheme, across a velocity range (<span><math><msub><mrow><mi>V</mi></mrow><mrow><mi>m</mi></mrow></msub></math></span>) from <span><math><mn>1.018</mn></math></span> to <span><math><mrow><mn>1.503</mn><mspace></mspace><mrow><mrow><mi>m</mi></mrow><mo>/</mo><mrow><mi>s</mi></mrow></mrow></mrow></math></span> and a corresponding Froude number range (<span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>n</mi></mrow></msub></math></span>) from <span><math><mn>0.126</mn></math></span> to <span><math><mn>0.186</mn></math></span>. The study employs an unstructured hexahedral grid, coupled with <strong><u>W</u></strong>all <strong><u>F</u></strong>unction (WF) and <strong><u>W</u></strong>all <strong><u>R</u></strong>esolved (WR) approaches, and conducts a grid independence analysis to assess numerical uncertainty of the CFD simulations, validating hull resistance predictions against EFD data and ensuring compliance with relevant International Towing Tank Conference (ITTC) guidelines. The key findings highlight the significant influence of turbulence model choice and near-wall treatment (WF or WR) on prediction accuracy, underscoring the importance of an integrated approach to simulation requirements, flow characteristics, accuracy standards, and computational resources for reliable numerical results. Finally, based on Oceanbeauty’s CFD resistance prediction, the generalization of the results to diverse hull forms, with different design parameters, is presented and discussed.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"138 ","pages":"Pages 1-20"},"PeriodicalIF":6.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Security resource allocation algorithm for RIS assisted NOMA-UAV networks with statistical CSI of eavesdropper","authors":"Zhengqiang WANG ,&nbsp;Yumeng SUN ,&nbsp;Siyu QING ,&nbsp;Yongjun XU ,&nbsp;Chengyu WU","doi":"10.1016/j.aej.2026.01.040","DOIUrl":"10.1016/j.aej.2026.01.040","url":null,"abstract":"<div><div>To enhance the security of communication systems, we propose a resource allocation algorithm for unmanned aerial vehicle (UAV)-assisted non-orthogonal multiple access (NOMA) networks utilizing a reconfigurable intelligent surface (RIS), aiming to maximize the minimum secure rate. The algorithm considers constraints on UAV maximum transmit power, RIS phase shifts, successive interference cancellation (SIC) decoding order, and security outage probability. By leveraging statistical channel state information (CSI) from eavesdropping channels, we formulate a joint optimization model for UAV transmit power, RIS phase shifts, and SIC decoding order. We obtain a precise formula for the security outage probability and convert probabilistic constraints into deterministic constraints. Subsequently, we propose an iterative algorithm based on block coordinate descent, transforming the problem into a convex optimization framework using techniques such as variable substitution, penalty functions, and successive convex approximation for an efficient solution. Simulation results demonstrate that the proposed algorithm significantly enhances the minimum secure rate. Specifically, it achieves performance improvements of 10.3 %, 64.9 %, and 99.5 % over the NOMA without RIS scheme, the OMA with RIS scheme, and the OMA without RIS scheme, respectively. This approach represents a significant advancement in ensuring robust and secure communication in UAV-assisted NOMA networks with RIS integration.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"138 ","pages":"Pages 141-151"},"PeriodicalIF":6.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Rotationally symmetric resonator-based metamaterial for wideband EMI shielding and blood dielectric property sensing applications","authors":"Abdullah Al Mahfazur Rahman ,&nbsp;Mohamad A. Alawad ,&nbsp;Md. Moniruzzaman ,&nbsp;Yazeed Alkhrijah ,&nbsp;Badariah Bais ,&nbsp;Abdulmajeed M. Alenezi ,&nbsp;Mohammad Tariqul Islam","doi":"10.1016/j.aej.2026.01.021","DOIUrl":"10.1016/j.aej.2026.01.021","url":null,"abstract":"<div><div>This paper presents a rotationally symmetric metamaterial (MTM) designed for electromagnetic interference (EMI) shielding and blood dielectric sensing applications. The geometry of the MTM unit cell (<span><math><mrow><mn>9.6</mn><mi>mm</mi><mo>×</mo></mrow></math></span> <span><math><mrow><mn>9.6</mn><mi>mm</mi><mo>×</mo><mn>1.6</mn><mi>mm</mi></mrow></math></span>) is optimized through CST simulation. The array of unit cells ensures the S₂₁ resonance at 5.961 GHz, with a broader bandwidth of 4.28 GHz (71.80 %) spanning from 3.75 to 8.03 GHz for the optimized dimensions of various segments of the rotationally symmetric unit cell. Utilizing field distribution, surface current, and effective parameter responses, the resonance phenomena are analyzed. The array structure of the MTM achieves a peak shielding effectiveness of 39.78 dB within the C-band while maintaining angular stability. Additionally, it performs nonlinear sensing responses, establishing a high-frequency deviation ranging from 4.037 to 4.230 GHz and demonstrating a high sensitivity of 4.44 %, which enables it to detect variations in blood dielectric properties. For sensing analysis, samples are replicated in a laboratory to accurately imitate blood dielectric properties. The performance of the designed MTM is validated by prototype measurements, which align well with the simulations. The findings confirm the design's effectiveness for EMI shielding in microwave communication and its potential for blood dielectric sensing in biomedical applications.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"137 ","pages":"Pages 101-122"},"PeriodicalIF":6.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid extractive–abstractive summarization of scientific texts via deep clustering and attention mechanism","authors":"Sammer Sami Abdulkareem,&nbsp;Mohammad-Reza Feizi-Derakhshi","doi":"10.1016/j.aej.2026.01.051","DOIUrl":"10.1016/j.aej.2026.01.051","url":null,"abstract":"<div><div>Scientific document summarization presents unique challenges due to domain-specific terminology, long-form discourse, and high compression demands. We propose a novel hybrid summarization model that combines deep clustering-based extractive scoring with an attention-guided abstractive generator. Sentence embeddings are clustered to capture semantic structure, and their importance is estimated via an MLP-based scoring system augmented with cluster-level weighting. These representations are then passed to a cross-attention-driven transformer-based decoder, enabling contextualized summary generation. Evaluated on ArXiv and PubMed datasets, our model surpasses BART, PEGASUS, and T5 in both ROUGE and BLEU metrics. Ablation studies confirm the critical role of clustering, scoring, and fusion components. Our approach bridges extractive precision and abstractive richness, demonstrating promising applicability in assisting researchers with scientific information overload.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"138 ","pages":"Pages 21-35"},"PeriodicalIF":6.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From policy frameworks to AI mentoring practice: A structured approach to responsible innovation in architectural education","authors":"Hosam Salah El Samaty ,&nbsp;Noorh Albadi","doi":"10.1016/j.aej.2026.01.012","DOIUrl":"10.1016/j.aej.2026.01.012","url":null,"abstract":"<div><div>Addressing the policy-to-practice gap in AI-supported architectural education, this study examines a structured “AI Mentoring Method” in alignment with King Abdulaziz University’s AI policy framework. Implemented in a senior undergraduate architectural research course across two consecutive semesters under different instructors, the method is organized into three stages: design, application, and evaluation, and systematically integrated across five course chapters. Generative AI tools were embedded through instructor-mediated tasks grounded in guided inquiry, scaffolding, and reflective practice. The study adopts an explanatory case study approach combining student satisfaction surveys, longitudinal quantitative assessment of Intended Learning Outcomes, and qualitative evidence from student work samples. Survey data were analyzed descriptively, while learning outcomes were compared across three semesters (pre-implementation and post-implementation under two instructors). Results indicate improved AI literacy, sustained learning gains, and strengthened value-based outcomes related to ethical awareness and academic responsibility. Variations between cohorts highlight the critical role of the instructor in shaping AI-supported learning, despite applying the same methodological framework. The study contributes a pedagogically grounded and policy-aligned model for responsible AI integration. While limited by a single-course context, the findings suggest that the AI Mentoring Method offers a transferable framework for structured, instructor-led AI adoption in design and research-based curricula.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"137 ","pages":"Pages 206-217"},"PeriodicalIF":6.8,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146036718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}