alexandria engineering journal最新文献

{"title":"Spatio-temporal few-shot traffic flow prediction based on transfer learning and graph convolutional neural networks","authors":"Dongxue Wang ,&nbsp;Chen Xu ,&nbsp;Hongguo Cai","doi":"10.1016/j.aej.2026.04.045","DOIUrl":"10.1016/j.aej.2026.04.045","url":null,"abstract":"<div><div>Addressing the intricate challenges posed by the hidden, complex, and dynamic spatial-temporal correlations and heterogeneity within traffic flow data is crucial for achieving high-precision traffic flow prediction. The introduction of new traffic nodes and roads exacerbates these challenges due to the limited sample sizes available, leading to a scarcity of historical data necessary for accurate prediction models or training. To address the practical problem of insufficient training data for traffic flow prediction in emerging cities, new traffic nodes, or sensor-sparse areas, this paper proposes a Transfer Learning and Dynamic Graph Convolutional Neural Network (TL-DGCNN) model based on transfer learning and graph convolutional neural network, which captures spatial dependencies and complex dynamic spatial relationship networks in traffic data, including dynamic and static features. Through the implementation of a dynamic adaptive graph convolution powered by an attention mechanism, the TL-DGCNN model effectively addresses the challenge of significant knowledge transfer loss due to drastic variations in traffic data distribution. The model achieves 13.1% lower MAE, 15.2% lower MAPE, and 8.2% lower RMSE on the PEMS-BAY dataset, and 12.1% lower MAE, 16.0% lower MAPE, and 7.0% lower RMSE on the METR-LA dataset compared to the best baseline model; paired t-test (α=0.05) verifies that the performance improvement is statistically significant (p &lt; 0.05). The experimental results validated the accuracy and robustness of the model in traffic flow scenarios with scarce data and limited samples, demonstrating its ability to significantly improve predictive performance. Moreover, TL-DGCNN maintains lower computational complexity and inference latency while achieving superior prediction accuracy, realizing an excellent trade-off between accuracy and complexity for practical deployment. This study provides practical support for intelligent transportation system construction, helping traffic management departments implement dynamic scheduling and optimize resource allocation, while enriching few-shot learning methods in the field of intelligent transportation.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"144 ","pages":"Pages 175-189"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147804819","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":"Efficient blockchain-based knowledge data sharing with All-or-Nothing Transform threshold secret scheme","authors":"Philip Kwaku Adjei ,&nbsp;Qin Zhiguang ,&nbsp;Isaac Amankona Obiri ,&nbsp;Christian Nii Aflah Cobblah ,&nbsp;Ansu Badjie ,&nbsp;Ali Alqahtani ,&nbsp;Yeong Hyeon Gu ,&nbsp;Mugahed A. Al-antari","doi":"10.1016/j.aej.2026.04.042","DOIUrl":"10.1016/j.aej.2026.04.042","url":null,"abstract":"<div><div>The increasing reliance on decentralized infrastructures for knowledge management necessitates secure, scalable, and efficient data sharing mechanisms. This paper proposes an efficient blockchain-based knowledge data sharing framework that combines the Greedy Threshold Set Cover Protocol (Greedy TSCP) with an All-or-Nothing Transform (AONT) to form a novel threshold secret sharing scheme without encryption. The scheme addresses the limitations of traditional polynomial-based and modular arithmetic approaches by offering lightweight computation and eliminating the need for interpolation. We formalize the security guarantees of the proposed GreedyTSCP-AONT scheme under the Universally Composable (UC) framework, providing an ideal functionality and proving its realization against static adversaries (who fix the set of corrupted servers before the protocol begins) and rushing adversaries (who may delay honest-party messages within the bounded-delay network model). The construction achieves information-theoretic security and leverages decentralized storage nodes to avoid single points of failure, while blockchain integration ensures transparency, tamper resistance, and auditability. The scheme is especially suited for large-scale knowledge data sharing in distributed environments, where conventional secret sharing schemes become computationally infeasible. Experimental evaluations show notable efficiency improvements over Shamir-based and Chinese Remainder Theorem (CRT)-based methods, demonstrating the practical viability of our approach for secure, high-throughput knowledge dissemination.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 44-62"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806757","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":"Controlling the direction and magnitude of spontaneous emission using a symmetrical closed quantum cavity","authors":"S. Al-Awfi","doi":"10.1016/j.aej.2026.04.058","DOIUrl":"10.1016/j.aej.2026.04.058","url":null,"abstract":"<div><div>Spontaneous emission into micro- or nano-scale structures can be enhanced or inhibited by engineering the local density of optical states using closed quantum cavities. When electromagnetic fields are confined within small mode volumes of a high-Q symmetrical closed quantum cavity, the Purcell effect significantly accelerates the natural spontaneous emission. Due to the statistical nature of spontaneous emission, the emitted fields do not have a well-defined phase; consequently, the emission is incoherent and lacks directional control. The situation becomes more complicated in multi-mode cavities, as selecting a specific mode in a particular direction requires precise detuning between the emitter transition frequency and the cavity mode frequency to ensure strong coupling. In single-mode cavities, only the dominant mode can resonate, and only in a specific direction; thus, an appropriate transition frequency range can be easily determined. Such cavities allow for greater manipulation of the local electromagnetic density of states, facilitating effective control of the direction of spontaneous emission. This property is essential for creating efficient single-photon sources, photonic circuits, and on-chip quantum information.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 97-102"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806677","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":"A multi-scale feature enhancement and context-aware convolutional network for small object detection in remote sensing images","authors":"Laomo Zhang ,&nbsp;Ying Ma ,&nbsp;Guowei Li ,&nbsp;Tianrui Li ,&nbsp;Wendi Yang","doi":"10.1016/j.aej.2026.04.043","DOIUrl":"10.1016/j.aej.2026.04.043","url":null,"abstract":"<div><div>In remote sensing imagery, detecting extremely small objects is inherently challenging due to severe scale imbalance, sparse pixel representation, and complex background interference. In high-resolution aerial scenes, targets often occupy only a few pixels, which weakens feature responses and leads to unstable optimization. Although multi-scale detection architectures partially alleviate this issue, they often lack mechanisms for structural enhancement and scale-aware supervision. To address these challenges, CEMF-Net is proposed, a unified detection framework that integrates frequency-guided multi-scale modeling, context-selective feature modulation, and scale-consistent label assignment. By enhancing high-frequency structural cues and incorporating scale alignment into the supervision process, the proposed framework improves feature representation and localization stability for tiny objects in complex aerial environments. Extensive experiments on AI-TOD, DOTA-v1.5, and VisDrone demonstrate consistent performance gains across diverse benchmarks. On AI-TOD, CEMF-Net achieves 67.3% [email protected] and 54.6% <span><math><mrow><mi>A</mi><msub><mrow><mi>P</mi></mrow><mrow><mi>s</mi><mi>m</mi><mi>a</mi><mi>l</mi><mi>l</mi></mrow></msub></mrow></math></span>, highlighting its effectiveness for detecting extremely small objects. These results demonstrate the effectiveness of CEMF-Net as a unified framework for remote sensing small object detection, with potential value for practical applications such as UAV traffic monitoring, maritime surveillance, and emergency response.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"144 ","pages":"Pages 129-142"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147804835","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":"Corrigendum to “SAMFNet: Scene-aware sampling and multi-stage fusion for multimodal 3D object detection” [Alex. Eng. J. 126 (2025), 90–104]","authors":"Baotong Wang ,&nbsp;Chenxing Xia ,&nbsp;Xiuju Gao ,&nbsp;Bin Ge ,&nbsp;Kuan-Ching Li ,&nbsp;Xianjin Fang ,&nbsp;Yan Zhang ,&nbsp;Yuan Yang","doi":"10.1016/j.aej.2026.04.013","DOIUrl":"10.1016/j.aej.2026.04.013","url":null,"abstract":"","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"143 ","pages":"Page 237"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147799118","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":"Mathematically structured quantum time-series analytics with dual-stream convolutional recurrent network for advanced smart grid fault detection","authors":"Iyad Katib ,&nbsp;Mahmoud Ragab ,&nbsp;Sanaa A. Sharaf ,&nbsp;Wafi Bedewi ,&nbsp;Emad Albassam ,&nbsp;Abdullah A. Al-Ghamdi","doi":"10.1016/j.aej.2026.04.033","DOIUrl":"10.1016/j.aej.2026.04.033","url":null,"abstract":"<div><div>Deep learning models are used to identify fault type, recognize fault location, and find out faulty portions, learns emerging failures and their reasons, and predict the fault patterns. Quantum machine learning connects the gap between theoretical developments in quantum computing and applications in machine learning. In general, it shows the combination of significant ML techniques in a quantum module. This article proposes a Quantum Time-Series Analytics Framework for Advanced Smart Grid Fault Detection. This work aims to develop an intelligent system capable of precisely detecting and classifying diverse types of faults in smart grid systems. The raw data are initially pre-processed to enhance data quality and ensure reliable model training. A quantum approximate optimization algorithm-based feature selection algorithm is applied to identify the best subset of features. The selected features are then passed to a dual-stream convolutional recurrent network for accurate smart grid fault detection. The learning performance and convergence stability of the proposed architecture are enhanced by employing the AdaBelief optimizer. The experimental result analysis of the QTSA-ASGFD technique was conducted using a smart grid monitoring dataset, and the results were evaluated under various aspects. The simulation analysis demonstrated the superiority of the QTSA-ASGFD technique over recent state-of-the-art methods.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 85-96"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806678","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":"A multifunctional fluorescent probe FTU for simultaneous detection of Hg²⁺and F⁻: Insights from theoretical studies","authors":"Yu-ling Liu ,&nbsp;Yue Deng ,&nbsp;Jian Feng ,&nbsp;Yong-jin Peng ,&nbsp;Liang Fu","doi":"10.1016/j.aej.2026.04.047","DOIUrl":"10.1016/j.aej.2026.04.047","url":null,"abstract":"<div><div>This study reported the development of a novel fluorescent probe, FTU, capable of selectively detecting Hg²⁺and F⁻ions in aqueous solutions. The probe exhibited distinct spectral responses to both ions, characterized by red shifts in absorption wavelengths and changes in fluorescence intensity. Quantum chemical calculations revealed that FTU existed in two low-energy conformations (FTU-A and FTU-B) with different reactivity toward Hg²⁺and F⁻. Specifically, F⁻forms hydrogen-bonded complexes (FTU-FA and FTU-FB) with varying binding energies (IGMH isosurface volumes: 1.2 ų vs 0.8 ų), where FTU-FA retained strong fluorescence due to local excitation, while FTU-FB underwent charge transfer, leading to weak fluorescence. In contrast, Hg²⁺bound to two FTU molecules (FTU-HgA and FTU-HgB), forming stable complexes via van der Waals interactions (IGMH volumes: 11.6 ų vs. 3.8 ų), both of which suppress fluorescence through charge transfer. In addition, the conformations FTU-FC formed by F⁻ abstracting the H atom of the N–H bond to eliminate HF and FTU-HgC formed by Hg²⁺ binding with the S atom to eliminate HgS were also calculated in this work. Meanwhile the simulated UV-Vis spectra are quantitatively consistent with experimental results, validating the reliability of theoretical models. The theoretical predictions aligned well with experimental observations, providing a mechanistic understanding of the probe’s dual-ion detection capability. This work highlighted the potential of rationally designing multifunctional probes by leveraging conformational diversity and electronic structure.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 77-84"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806679","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 role of austenitic butter layers in modifying impact behavior of hardfaced high-strength steels","authors":"Ákos Meilinger,&nbsp;Gábor Terdik","doi":"10.1016/j.aej.2026.04.053","DOIUrl":"10.1016/j.aej.2026.04.053","url":null,"abstract":"<div><div>Hardfacing is commonly used to improve surface wear resistance; however, it may reduce substrate toughness due to microstructural changes in the heat-affected zone. To mitigate this effect, an austenitic stainless steel butter layer is often applied between the high-strength steel substrate and the hardfacing layer. In this study, the influence of the butter layer and heat input on impact behavior was investigated for S690QL, S960QL, and S1100QL steels using instrumented Charpy impact testing. Microstructural characterization was performed by optical and scanning electron microscopy, supported by hardness mapping on cross-sections. The presence of the austenitic butter layer significantly reduced the absorbed impact energy for S690QL and S960QL, while increasing it for S1100QL. In general, increasing heat input resulted in lower impact energy and higher peak impact force. The best performance was obtained for S960QL processed with low heat input, showing a 132% increase in impact energy, whereas S1100QL exhibited the lowest impact energy under the same condition; however, at the highest heat input, the impact energy of S1100QL increased by 113%. These findings are particularly relevant for demolition shears, where components are typically subjected to dynamic loading, and highlight the importance of optimizing substrate - butter layer combinations and hardfacing parameters.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 29-43"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806758","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":"YOLOv8-GSC: An agricultural crop precision detection model integrating lightweight network and attention mechanism","authors":"Wenzheng Dai,&nbsp;Zhanhui Zhang,&nbsp;Zhixin Zhang,&nbsp;Huashuo Zhu","doi":"10.1016/j.aej.2026.04.027","DOIUrl":"10.1016/j.aej.2026.04.027","url":null,"abstract":"<div><div>Visual perception and agricultural target recognition are core to advancing agricultural automation, yet existing CNN-based detection models face critical accuracy-efficiency trade-offs in scenarios with multi-scale targets and cluttered backgrounds. To address this, we propose YOLOv8-GSC, an improved model integrating YOLOv8 with three key modules in a synergistic manner—distinct from simple module superposition. GhostNet reduces redundant computations for model lightweighting; Spatial and Channel Reconstruction Convolution (SCConv) enhances fine-grained feature extraction for small targets like crop lesions; and Polarized Multi-Scale Attention (PMSA) enables multi-scale attention to capture targets of varying sizes. Experiments on PlantVillage and Agriculture-Vision datasets demonstrate that YOLOv8-GSC outperforms comparative models, achieving mean Average Precision at 50% IoU (mAP50) of 77.6% and 74.05%, and mean Average Precision at 75% IoU (mAP75) of 49.8% and 47.63%, respectively. It maintains high inference speed, realizing an optimal balance between accuracy and efficiency, and effectively tackles key agricultural detection challenges, providing reliable technical support for crop disease monitoring and precision farming.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 63-76"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806756","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":"A critical review of microwave and conventional pyrolysis technologies for biomass and plastic waste conversion","authors":"Anuradha K,&nbsp;Ranjeet Kumar Mishra","doi":"10.1016/j.aej.2026.04.046","DOIUrl":"10.1016/j.aej.2026.04.046","url":null,"abstract":"<div><div>This comprehensive review examines the current state and future potential of microwave and conventional pyrolysis, emphasising the significance of process parameters in facilitating sustainable resource recovery from biomass and plastics. A detailed assessment of process variables, including temperature, residence time, and feedstock composition, is essential to this evaluation and to determining the yields and quality of pyrolysis products. The review highlights the intricate interactions among these factors and their critical role in achieving optimal resource recovery. The major focus of the review is the comparison of conventional pyrolysis methods with the microwave-assisted techniques. The well-established processes of traditional pyrolysis are contrasted with the rapid, accurate heating capabilities of microwave technology. This comparison demonstrates the potential of microwave-assisted pyrolysis to enhance energy efficiency and resource recovery. The discussion focuses on identifying current knowledge gaps and defining key opportunities for future research, with particular attention to integrating biomass and plastic pyrolysis into sustainable resource recovery approaches. The review contributes to the ongoing discourse on advancing pyrolysis technologies to support a more sustainable, circular economy by synthesising current knowledge and projecting future opportunities. The current review highlights the potential of conventional and microwave-assisted pyrolysis for sustainable resource recovery in a clear, detailed manner.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"145 ","pages":"Pages 103-136"},"PeriodicalIF":6.8,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147806759","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}