alexandria engineering journal最新文献

{"title":"A culturally-inspired quad-band qing-shaped patch antenna with quadrant-quadrant-swipe feed optimization","authors":"Kwok L. Chung ,&nbsp;Yingqi Pei ,&nbsp;Zhilie Tang ,&nbsp;Caiying Li ,&nbsp;Hongming Zhang","doi":"10.1016/j.aej.2025.09.047","DOIUrl":"10.1016/j.aej.2025.09.047","url":null,"abstract":"<div><div>This communication introduces a novel natural design technique for microstrip patch antennas, exemplified by the Qing(情)-shaped patch antenna inspired by Lisu calligraphy. The unique shape of the Qing symbol, representing deep emotional bonds and interconnectedness, significantly influences the antenna's electromagnetic properties. Unlike conventional patch antennas, the Qing-shaped patch operates across four distinct frequency bands (1.7, 2.1, 2.6, and 3.0 GHz) with peak gains of 7.84 dBi, 8.4 dBi, 5.6 dBi, and 8.0 dBi, respectively, in unidirectional radiation. The design leverages the unique shape of the Qing symbol to create distinct resonant modes, as revealed by surface current distributions and radiation patterns. The Quadrant-Quadrant-Swipe (QQS) technique was employed to determine the optimal feed location, enhancing performance. This natural design approach offers a unique solution for multiband applications, integrating cultural heritage with modern antenna engineering.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"131 ","pages":"Pages 1-6"},"PeriodicalIF":6.8,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145236186","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":"Hahn polynomials method for ψ-Caputo fractional diffusion-wave equation involving damping and reaction terms","authors":"M.H. Heydari ,&nbsp;M.A. Zaky ,&nbsp;D. Baleanu ,&nbsp;M. Bayram","doi":"10.1016/j.aej.2025.09.039","DOIUrl":"10.1016/j.aej.2025.09.039","url":null,"abstract":"<div><div>In this paper, the <span><math><mi>ψ</mi></math></span>-Caputo derivative is employed to develop a novel formulation of the fractional 2D diffusion-wave equation, incorporating damping and reaction terms. To solve this equation efficiently, a collocation algorithm is designed using the orthonormal discrete Hahn polynomials (ODHPs). A key component of this approach is the construction of a fractional integral matrix for the ODHPs, which plays a crucial role in the numerical solution process. By representing the fractional derivative term through an ODHPs finite expansion, including several undetermined coefficients, and integrating the fractional matrix, the problem is transformed into an algebraic system of equations. More specifically, the undetermined coefficients are computed by solving this algebraic system, ultimately yielding the solution to the primary equation. The accuracy and effectiveness of the developed method are validated through three illustrative examples, demonstrating its reliability in handling fractional diffusion-wave equation.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 910-919"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217618","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":"Designing the recommendation algorithm for inheritance of intangible cultural heritage using wireless knowledge graphs and collaborative filtering","authors":"Caijuan Liu ,&nbsp;Xianhui Cui","doi":"10.1016/j.aej.2025.08.054","DOIUrl":"10.1016/j.aej.2025.08.054","url":null,"abstract":"<div><div>With the rapid progress in science and technology, wireless sensor networks are emerging as a dynamic field of innovation by offering robust potential for real-time data collection, intelligent decision-making, and seamless integration across smart environments. The online music education system can accommodate users’ different needs and behaviors in addition to realizing a variety of interactions. Because they make it possible to integrate various wireless technologies and devices seamlessly, wireless knowledge graphs can play a significant role in musical performance by giving musicians more autonomy and versatility. However, due to a large number of resources available to music performance groups and user characteristics that cannot be fully modeled, it takes time for consumers to find the necessary data quickly and easily. This paper presents a solution to facilitate users when seeking to find music performance data through the development of recommendation algorithm for music performance based on a wireless knowledge graph (WKG) and collaborative filtering. Fascinating user behavioral signals, like preferences, context and interaction histories are captured wirelessly to this goal and these signals are aligned to a WKG which encodes the semantic relations between artistic entities such as artists, genres and venues. User-relevant entity extraction module removes semantically aligned nodes from WKG as prescribed by the user and embeds them along with the user and item features into a common latent space through multi task learning. Through the use of attention-based Graph-Convolutional Networks (GCNs) that support multi-hop aggregation, the embeddings are controlled to contain subtler semantic and relational dependencies in the graph. The integration of these features allows the interaction unit to estimate user–item interaction probabilities that in turn influence the general recommendation sequence. Optimization in the system is realized through a collaborative reduction of recommendation loss, knowledge embedding loss, and regularization costs with cross-compression methods. Analysis on standard datasets indicates that the proposed model outperforms DKN, MKR, and CKE in superior AUC liftups of 20.2% and 17.5% accuracy increases on Last.FM and 12.1% AUC growth on Book-Crossing. Moreover, the model is very robust to lack of data, and systematically outperforms in terms of Precision and Recall confirming its usability for context-aware Top-K music recommendations.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 875-888"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217616","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":"Stochastic fractional order solution of buck converter with uncertain parameters","authors":"Khalid Saleh ,&nbsp;Osama H. Galal","doi":"10.1016/j.aej.2025.09.056","DOIUrl":"10.1016/j.aej.2025.09.056","url":null,"abstract":"<div><div>This study introduces a novel Monte Carlo-based analysis of parameter uncertainties in fractional-order buck converters, systematically evaluating their sensitivity to individual variations in the fractional inductor, capacitor, and load, as well as their combined interactions. The results show that inductor uncertainties yield asymmetric voltage distributions with left-tailed characteristics, exhibiting the smallest impact on the mean and standard deviation of the voltage. The capacitor variations lead to symmetric fluctuations with moderate mean shifts below 2.8 %. Load variations exhibit the most significant impact, generating extreme output ranges of 0.5917. When combined, these uncertainties create nonlinear interactions that result in peaked distributions at specific frequencies, particularly near 12.8 krad/s, with substantially widened operational bounds. A critical vulnerability window emerges during the system's transition phase between <span><math><msup><mrow><mn>7.70</mn><mo>×</mo><mn>10</mn></mrow><mrow><mn>2</mn></mrow></msup></math></span> and <span><math><msup><mrow><mn>6.46</mn><mo>×</mo><mn>10</mn></mrow><mrow><mn>5</mn></mrow></msup></math></span> rad/s, where parameter uncertainties have their greatest effect. The comprehensive statistical analysis, including probability density functions, standard deviations, and output voltage bounds, provides valuable quantitative guidelines for converter design. The study offers practical insights for developing robust fractional power electronic systems capable of reliable operation under real-world parameter variations, establishing clear safety margins for component tolerances and operational frequency ranges.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 944-953"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217625","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":"Adaptive quasi-opposition and dynamic switching in black-winged kite algorithm for global optimization and constrained engineering designs","authors":"Rajasekar P.,&nbsp;Jayalakshmi M.","doi":"10.1016/j.aej.2025.09.058","DOIUrl":"10.1016/j.aej.2025.09.058","url":null,"abstract":"<div><div>The Black-winged Kite Algorithm (BKA) is a bio-inspired optimization algorithm that mimics the migratory and predatory behaviors of the black kite to find global solutions to complex optimization problems. However, BKA suffers from issues such as stagnation at local minima and slow convergence. To address these challenges, we propose two key enhancements. First, we introduce adaptive quasi opposition-based learning in both the initialization and iterative phases, enabling the algorithm to explore a broader and more diverse solution space from the outset. Second, a dynamic switching mechanism is implemented to adaptively balance exploration and exploitation throughout the search process. The resulting approach, named Adaptive Quasi Opposition and Dynamic Switching in Black-winged Kite Algorithm (AQODSBKA), is evaluated on 23 standard benchmark functions, 10 CEC2019 test functions, and 5 real-world engineering design problems. Comparative analysis, supported by statistical tests, demonstrates that AQODSBKA outperforms the original BKA and other well-established algorithms in terms of accuracy and convergence speed, while preserving the algorithm’s simplicity.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 969-994"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217628","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":"How PCA helps multi-criteria decision making for feature selection: A feature fusion approach in bioinformatics and gene expression data","authors":"Mohsen Habibollahi ,&nbsp;Amin Hashemi ,&nbsp;Mohammad Bagher Dowlatshahi ,&nbsp;Marjan Kuchaki Rafsanjani ,&nbsp;Varsha Arya ,&nbsp;Brij B. Gupta","doi":"10.1016/j.aej.2025.09.028","DOIUrl":"10.1016/j.aej.2025.09.028","url":null,"abstract":"<div><div>In high-dimensional data analysis, unsupervised feature selection plays a crucial role in enhancing model interpretability and reducing computational cost. While Principal Component Analysis (PCA) and Multi-Criteria Decision-Making (MCDM) methods such as MOORA have individually been employed for dimensionality reduction and feature evaluation, their combined use remains underexplored in the context of unsupervised feature selection. This study proposes a structured hybrid approach that integrates PCA for extracting dominant components and MOORA for ranking original features based on their alignment with those components. Unlike traditional methods that rely on a single criterion or lack interpretability, our fusion method incorporates multiple decision metrics in a unified framework. The proposed approach is evaluated on both bioinformatics datasets and diverse real-world applications, demonstrating consistent improvements in classification accuracy and feature reduction compared to standalone PCA, MOORA, and other baseline techniques. These results suggest that the synergy between PCA and MCDM can provide a more robust and generalizable strategy for unsupervised feature selection across domains.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 809-826"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217614","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":"Comparison of flow characteristics and performance between horizontally oriented hybrid hydrokinetic turbine rotors","authors":"Can Kang ,&nbsp;Xiaoyu Jia ,&nbsp;Kejin Ding ,&nbsp;Yongchao Zhang ,&nbsp;Hyoung-Bum Kim","doi":"10.1016/j.aej.2025.09.063","DOIUrl":"10.1016/j.aej.2025.09.063","url":null,"abstract":"<div><div>The present study aimed to reveal the operation and flow characteristics of horizontally oriented hybrid hydrokinetic turbine rotors composed of Bach and H rotors. The computational fluid dynamics (CFD) technique was used in conjunction with the six degrees of freedom (SDOF) method to solve instantaneous flow field. The results indicate that at a tip speed ratio of 1.73, the highest power coefficient of 0.328 is obtained with the H(B) rotor, characterized by a Bach rotor encircled by the blades of an H rotor. For the H-B rotor, characterized by a Bach rotor arranged side by side with an H rotor, and the B-H-B rotor, which consists of Bach and H rotors arranged in series, their startup performance is similar, and their torque coefficients are about twice larger than that of the H(B) rotor. The rotational speed during the stable operation stage increases monotonically with the upstream flow velocity. The H(B) rotor features a shortest startup time of approximately 1.23 s at an upstream velocity of 2.8 m/s. A compound wake is evidenced by the H-B and B-H-B rotors; the part of the wake corresponding to the Bach rotor inclines downward, whereas the wake of the H rotor meanders in the streamwise direction. In comparison, the wake of the H(B) rotor involves a relatively high velocity deficit.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 827-840"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217619","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":"Advancing energy management using q-rung orthopair fuzzy prioritised multiparametric information measures","authors":"Hafiz Muhammad Athar Farid ,&nbsp;Shamaila Iram ,&nbsp;Hafiz Muhammad Shakeel ,&nbsp;Muhammad Riaz ,&nbsp;Vladimir Simic ,&nbsp;Erfan Babaee Tirkolaee","doi":"10.1016/j.aej.2025.09.041","DOIUrl":"10.1016/j.aej.2025.09.041","url":null,"abstract":"<div><div>The concept of q-rung orthopair fuzzy set (q-ROFS) is more useful in processing ambiguous information in multicriteria decision-making scenarios than the Pythagorean fuzzy set and intuitionistic fuzzy set. The main feature of q-ROFS data is that the membership grade, non-membership grade, and the sum of their qth-powers all lie in the unit closed interval <span><math><mrow><mo>[</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo>]</mo></mrow></math></span>. This feature provides decision-makers with a multitude of possibilities when deciding which grades to assign to the objects in the universe. This study presents new prioritised multiparametric information measures as well as their mathematical modelling and implementation for three-parameter q-ROFSs. Together with the corresponding similarity measures (SMs), the information measures multiparametric distance measure, multiparametric weighted distance measure, multiparametric prioritised distance measure, and multiparametric prioritised distance measure based on priority degree are proposed. In addition, some important instances are provided to discuss the practicality. We use the proposed SMs as the foundation for a unique multicriteria decision-making method. To further illustrate the efficacy and value of new SMs in energy management problems and energy-efficient technologies for a building project, two numerical examples are provided. We compare optimal outcomes with those of a few different SMs and aggregation operators to confirm the usefulness of the proposed approach.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 791-808"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217615","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":"Schweizer-Sklar power aggregation operators and EDAS model for circular interval-valued (p, q)-rung orthopair fuzzy sets & its application to green supply chain management","authors":"Harish Garg ,&nbsp;Zeeshan Ali ,&nbsp;Gia Sirbiladze ,&nbsp;Muhammad Usman ,&nbsp;Brij B. Gupta ,&nbsp;Ibrahim M. Hezam","doi":"10.1016/j.aej.2025.09.040","DOIUrl":"10.1016/j.aej.2025.09.040","url":null,"abstract":"<div><div>Lifecycle Assessment is an automatic and systematic technique used to address or ensure the ecological or green impacts linked with many of the phases of a product's life from raw substantial removal to recycling or disposal. In green supply chain management, lifecycle assessment plays a critical role in reducing, quantifying, and identifying environmental burdens throughout the supply chain. In this manuscript, we aim to assess the major role of the lifecycle assessment in green supply chain management; for this, we focus on the evaluation of the novel technique of circular interval-valued (p, q)-rung orthopair fuzzy information and develop or construct their important and basic operational laws for algebraic norms as well as for Schweizer-Sklar norms. Further, we presented some weighted averaging and geometric operators for both norms and hence discuss their fundamental properties. Later, we presented decision-making techniques named as “Evaluation based on Distance from the Average Solution” technique for solving the multi-attribute decision-making problems using the proposed operators. Finally, we clarify some numerical examples for the evaluation of the comparative analysis among the proposed ranking model with the ranking theory of prevailing information to describe the efficiency and rationality of the derived approaches.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 854-874"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217622","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":"Enhancing federated learning for IoT-based anomaly detection: A reputation-based client selection approach","authors":"Maha Jawad Alfadhil ,&nbsp;Ali Baydoun ,&nbsp;Moutaz Alazab ,&nbsp;Hafeez Ur Rehman ,&nbsp;Jihad Al Jaam ,&nbsp;Sumaya Ali S.A. Al-Maadeed","doi":"10.1016/j.aej.2025.09.019","DOIUrl":"10.1016/j.aej.2025.09.019","url":null,"abstract":"<div><div>Federated Learning (FL) enables collaborative model training across decentralized, privacy-sensitive environments but often suffers from slow convergence, unbalanced client selection, and non‑IID data challenges. We propose a Reputation‑Based Client Selection Mechanism with proportional fairness, computing each client’s reputation from accuracy, consistency, network conditions, data quality, and historical reliability. By adaptively prioritizing high‑contributing clients while ensuring equitable participation, our method accelerates convergence and balances contributions. Evaluations on the UNSW‑NB15 intrusion detection dataset under IID and non‑IID settings demonstrate that our approach significantly reduces the number of communication rounds needed to reach stable accuracy compared to FedAvg and FedProx, while enhancing model generalization and robustness. This scalable strategy advances FL for efficient, inclusive learning in IoT and cybersecurity.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"130 ","pages":"Pages 889-909"},"PeriodicalIF":6.8,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145217617","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}