alexandria engineering journal最新文献

{"title":"Bone tumor diagnosis: A FRET-based fluorescent osteocalcin sensor using palladium nanoparticles","authors":"Tao Wang ,&nbsp;Ke Zhang ,&nbsp;Mingyang Jiang ,&nbsp;Yinteng Wu ,&nbsp;Raquel Alarcón Rodríguez ,&nbsp;Shenyi Lu ,&nbsp;Ruqiong Wei","doi":"10.1016/j.aej.2025.02.021","DOIUrl":"10.1016/j.aej.2025.02.021","url":null,"abstract":"<div><div>This study was conducted on a design of a fluorescence resonance energy transfer (FRET)-based fluorescent osteocalcin sensor using palladium nanoparticles (PdNPs) and application for determining osteocalcin (OC) level as a bone turnover marker in human serum samples for bone tumor diagnosis. The PdNPs were synthesized via a seed-mediated growth method. The UV-Vis absorption spectrum of PdNPs and the fluorescence-emission spectrum of 5-carboxyfluorescein (FAM)-OC aptamer showed remarkable spectral overlap. FRET experiments were performed using a fixed concentration of 90 nM of FAM-labeled OC aptamer, and results indicated an OC concentration-dependent manner within the range of 5–1200 ng/mL with the limit of detection 0.31 ng/mL. The results showed the high recovery rates ranged from 97.70 % to 99.50 % with relative standard deviations between 3.37 % and 4.31 %, indicating the accuracy and reliability of the nanoprobe. The FRET-based aptamer nanoprobe showed excellent specificity towards OC, with minimal interference from other proteins. Additionally, it exhibited excellent long-term stability and repeatability, maintaining approximately 93.89 % of the initial FRET response after 25 days. These results suggested that the FRET-based aptamer nanoprobe is highly effective, reliable, and suitable for practical applications in clinical diagnostics.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 87-94"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387825","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":"Hybrid VTOL UAV technologies: Efficiency, customization, and sector-specific applications","authors":"Mohammed Osman ,&nbsp;Yuanqing Xia ,&nbsp;Mohammed Mahdi ,&nbsp;Azzam Ahmed","doi":"10.1016/j.aej.2024.12.087","DOIUrl":"10.1016/j.aej.2024.12.087","url":null,"abstract":"<div><div>The vertical take-off and landing (VTOL) drone is an innovative technology that offers enhanced operational flexibility by combining vertical take-off and landing capabilities with efficient forward flight, eliminating the need for runways. This review provides a comprehensive analysis of hybrid VTOL systems, focusing on their application-specific customization, efficiency improvements, and operational benefits. Special attention is given to the unique capabilities of tilt-rotor, tilt-wing, and dual systems for various sectors, including agriculture, surveying, and cargo transportation. By comparing current market offerings, this work aims to guide engineers and decision-makers in selecting optimal UAS platforms. Furthermore, recent advances in autonomous functions, material innovation, and 3D printing applications are also explored.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 13-49"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378718","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":"A new trigonometric-oriented distributional method: Model, theory, and practical applications","authors":"Omalsad Hamood Odhah ,&nbsp;Olayan Albalawi ,&nbsp;Huda M. Alshanbari","doi":"10.1016/j.aej.2025.01.096","DOIUrl":"10.1016/j.aej.2025.01.096","url":null,"abstract":"<div><div>In this study, a new family of distributions is proposed, which incorporates a trigonometric function and is termed the weighted tan-<span><math><mi>G</mi></math></span> family. In comparison to various alternative methods, a key advantage of the proposed approach is its lack of requirement for additional parameters. The research includes a thorough examination of numerous mathematical properties related to the weighted tan-<span><math><mi>G</mi></math></span> family. For demonstration purposes, a particular model from this family, called the weighted tan-Weibull distribution, is investigated. The Weibull model serves as the foundational framework for this specific variant. The maximum likelihood estimators for the parameters of the weighted tan-Weibull distribution are obtained. A concise simulation study is conducted to assess these estimators. Furthermore, two applications from distinct sectors are examined to illustrate the practicality of the weighted tan-Weibull distribution. The first application demonstrates the survival times of patients diagnosed with a certain medical condition, while the second application, sourced from the hydrological sector, represents the highest points of flood events. Utilizing various decision-making tools, the weighted tan-Weibull distribution exhibits enhanced performance, surpassing other established variants of the Weibull distribution.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 1-12"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378717","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 real-time data processing framework for blockchain and edge computing","authors":"Zhaolong Gao ,&nbsp;Wei Yan","doi":"10.1016/j.aej.2025.01.092","DOIUrl":"10.1016/j.aej.2025.01.092","url":null,"abstract":"<div><div>The rapid growth of IoT has increased the demand for large-scale data processing. However, traditional centralized methods struggle with real-time requirements and data security. This paper introduces VCD-TSNet, a novel real-time IoT data processing framework that combines blockchain and edge computing. By integrating deep learning models like VGG, ConvLSTM, and DNN, VCD-TSNet effectively performs spatial feature extraction, temporal modeling, and decision-making, while using blockchain to ensure data integrity and privacy. Experimental results demonstrate that VCD-TSNet outperforms baseline models in classification accuracy, prediction precision, and real-time performance. For instance, on the BoT-IoT dataset, the classification accuracy reaches 97.5%, throughput increases to 920 TPS, and response time stays below 85 ms. This study validates the model’s effectiveness and highlights its potential in large-scale IoT environments, offering efficient, secure solutions for real-time data processing. It also provides insights for future improvements in frameworks that combine edge computing with blockchain.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 50-61"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378719","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":"BACVC: Bi-adaptive and cross-view consistency for incomplete multi-view subspace clustering","authors":"Jiaqiyu Zhan,&nbsp;Yuesheng Zhu,&nbsp;Guibo Luo","doi":"10.1016/j.aej.2025.01.089","DOIUrl":"10.1016/j.aej.2025.01.089","url":null,"abstract":"<div><div>Multi-view subspace clustering leverages complementary information from different views to uncover latent subspaces. However, incomplete multi-view data is prevalent, particularly in fields such as communication systems. Incomplete Multi-View Subspace Clustering (IMSC) addresses this challenge but faces two main challenges: (1) neglecting dissimilarities between views and samples, and (2) insufficient handling of cross-view consistency. To tackle these issues, we propose a novel IMSC framework, referred to as Bi-Adaptive and Cross-View Consistency (BACVC). BACVC improves incomplete data recovery and subspace structure discovery through view-adaptive tensor rank constraints, data-adaptive high-order correlations, and view-level contrastive learning. Specifically, we first apply tensor factorization with view-adaptive tensor rank approximation to enforce low-rank constraints on a stacked affinity tensor, capturing the view-specific subspace block-diagonal structure. We then introduce a data-adaptive non-uniform hypergraph-induced hyper-Laplacian regularization to model high-order correlations and guide the recovery of incomplete data. Finally, contrastive learning is applied to the soft clustering assignment of each view, ensuring cross-view structural consistency. Extensive experiments on four benchmark datasets show that BACVC outperforms eleven state-of-the-art methods, with improvements of up to 4.39%, 5.43%, and 3.95% in ACC, NMI, and purity, respectively. Experimental results demonstrate the robustness of BACVC in handling incomplete data and its effectiveness in practical applications.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 623-633"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377920","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":"A genetic-based random ensemble forest learning for cloud-based automotive data transformation in internet of vehicle","authors":"Salwa Umar Qureshi ,&nbsp;Alireza Souri ,&nbsp;Nihat İnanç ,&nbsp;Jan Lansky ,&nbsp;Mehdi Hosseinzadeh","doi":"10.1016/j.aej.2025.01.120","DOIUrl":"10.1016/j.aej.2025.01.120","url":null,"abstract":"<div><div>The Internet of Vehicles (IoV) is a constantly changing field, and the fast convergence of automotive technology and connectivity has brought about a new era marked by enormous cybersecurity risks. A crucial component of the inquiry is a thorough examination of the IoV infrastructure's vulnerabilities, which highlights potential sources of compromise and places where strong cybersecurity measures are required for data transformations in cloud-edge computing. Additionally, the Controller Area Network (CAN) and the Electronic Control Units (ECUs) are critical points in automotive networking to connect user data from smart applications to electric vehicles. Therefore, finding a safe automotive data transformation approach for incorporating Connected and Autonomous Vehicles (CAVs) and investigating particular cybersecurity issues is a critical and key challenge in the IoV ecosystem. To ensure the safe development of the IoV landscape, the research introduces two innovative genetic algorithms, Genetic Algorithm Random Forest (GA-RF) and Genetic Algorithm Ensemble Bagged Trees (GA-EBT), to improve the identification of cyber threats in the IoV context. The simulation results demonstrate that the proposed hybrid algorithm achieves exceptional performance, attaining a high accuracy rate of 99.92 %, the lowest mean absolute error of 0.0028, and the highest precision, recall, and F1 measures near to 100 %. These results are especially noteworthy on real automotive data transformation datasets. These results highlight the significance of the suggested strategy for defending IoV systems from suspicious threats.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"120 ","pages":"Pages 74-86"},"PeriodicalIF":6.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378720","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":"Application of IoT and blockchain technology in the integration of innovation and industrial chains in high-tech manufacturing","authors":"Zepei Li ,&nbsp;Peng Zheng ,&nbsp;Yanjia Tian","doi":"10.1016/j.aej.2025.01.020","DOIUrl":"10.1016/j.aej.2025.01.020","url":null,"abstract":"<div><div>In industrial IoT (Internet of Things) environments, accurate anomaly detection and high-quality data management are crucial yet challenging due to noisy and incomplete sensor data. This study introduces BD-IoTQNet, a novel framework designed to address these challenges by integrating data fusion, anomaly detection using the Isolation Forest algorithm, and blockchain-enabled DQM (Data Quality Management). The framework leverages blockchain technology to ensure data transparency and security, while smart contracts automate exception handling to enhance efficiency. Experiments conducted on the NASA Turbofan Engine Degradation and UCI Hydraulic Systems datasets demonstrate that BD-IoTQNet outperforms existing models in accuracy, precision, and data quality improvement, with reduced latency and enhanced robustness under noisy and missing data conditions. An ablation study validates the critical role of each component, showing significant performance drops when modules like DQM or blockchain are excluded. These findings highlight BD-IoTQNet as an effective solution for improving anomaly detection, predictive maintenance, and operational efficiency in industrial IoT systems.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 465-477"},"PeriodicalIF":6.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377054","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":"Overcoming single-technology limitations in digital heritage preservation: A study of the LiPhoScan 3D reconstruction model","authors":"Yao Wang ,&nbsp;Wei Bi ,&nbsp;Xiaodong Liu ,&nbsp;Yan Wang","doi":"10.1016/j.aej.2024.12.095","DOIUrl":"10.1016/j.aej.2024.12.095","url":null,"abstract":"<div><div>With the increasing demand for the digital preservation of cultural heritage, high-precision 3D reconstruction of museum artifacts has become an important research direction. However, single technology approaches face limitations in practical applications, such as insufficient capture of geometric details, poor texture fidelity, and suboptimal geometric accuracy. To address these issues, this paper proposes the LiPhoScan hybrid 3D reconstruction model, which integrates LiDAR, photogrammetry, and structured light scanning technologies. This model leverages the high geometric accuracy of LiDAR, the high texture fidelity of photogrammetry, and the detail-capturing ability of structured light scanning to overcome the limitations of individual technologies, providing a more comprehensive and refined 3D reconstruction solution. Experimental results show that LiPhoScan improves geometric accuracy by 15% and texture fidelity by 20% compared to traditional methods. In addition, compared to existing single-technology approaches, LiPhoScan demonstrates significant advantages in detail fidelity and overall geometric consistency. This offers an innovative solution for the digital preservation of museum artifacts and lays a solid foundation for high-precision and high-detail 3D reconstruction tasks. Future research will incorporate parallel computing and efficient data processing methods to further enhance the model’s computational efficiency.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 518-530"},"PeriodicalIF":6.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377110","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":"Evaluating pre-processing and deep learning methods in medical imaging: Combined effectiveness across multiple modalities","authors":"Thien B. Nguyen-Tat ,&nbsp;Tran Quang Hung ,&nbsp;Pham Tien Nam ,&nbsp;Vuong M. Ngo","doi":"10.1016/j.aej.2025.01.090","DOIUrl":"10.1016/j.aej.2025.01.090","url":null,"abstract":"<div><div>Medical imaging is critical in modern healthcare for accurately detecting and diagnosing various medical conditions. Advanced computational techniques, particularly preprocessing methods and deep learning models, have demonstrated significant potential for improving medical image analysis. However, determining the optimal combination of these techniques across different types of medical images remains a challenge. Using empirical experiments, this evaluation research investigates the effectiveness of five popular pairs of preprocessing techniques combined with five widely used deep learning models. Preprocessing methods evaluated include CLAHE + Butterworth, DWT + Threshold, CLAHE + median filter, Median-Mean Hybrid Filter, and Unsharp Masking + Bilateral Filter, concatenated with deep learning models: EfficiencyNet-B4, ResNet-50, DenseNet-169, VGG16 and MobileNetV2. The performance of these combinations was evaluated through experiments carried out on eight diverse and commonly used datasets encompassing various medical imaging modalities. These datasets include two X-ray collections: the COVID-19 Pneumonia Normal Chest PA Dataset and the Osteoporosis Knee X-ray Dataset; two CT scan datasets: the Chest CT-Scan Images Dataset and the Brain Stroke CT Image Dataset; two MRI datasets: the Breast Cancer Patients MRI and the Brain Tumor MRI Dataset; and two ultrasound datasets: the Ultrasound Breast Images for Breast Cancer and the MT Small Dataset. Our findings show that the Median-Mean Hybrid Filter and Unsharp Masking + Bilateral Filter are the most effective preprocessing methods, achieving an efficiency rate of 87.5%. Among the deep learning models, EfficiencyNet-B4 and MobileNetV2 are the highest performing models with an efficiency ratio of 75%, with MobileNetV2 providing up to 34% shorter runtime compared to other models. This study provides a thorough evaluation of the performance of different preprocessing methods and deep learning algorithms across commonly used medical imaging modalities. Presenting empirical results from our experiments offers practical insights into choosing the most suitable preprocessing techniques and deep learning models for various types of medical images. These findings are intended to support improvements in diagnostic accuracy and efficiency in medical imaging, offering a valuable reference for enhancing image-based diagnostic processes.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 558-586"},"PeriodicalIF":6.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377119","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":"New super and shock like solitary structures for KdV equation with higher-order nonlinearity","authors":"H.S. Alayachi ,&nbsp;Abdulghani Alharbi ,&nbsp;E.K. El-Shewy ,&nbsp;Mahmoud A.E. Abdelrahman","doi":"10.1016/j.aej.2025.01.124","DOIUrl":"10.1016/j.aej.2025.01.124","url":null,"abstract":"<div><div>The model of dual-power law nonlinearity Korteweg–De Vries (KdV) equation describe sudden physical phenomena with higher orders of nonlinearity in fluid dynamics, plasma, fiber communications and biological systems. The model was solved by the modified F-expansion approach to produce structural solutions in the vital form of super periodic solitons, super periodic shocks, shock solutions, super-shock-soliton like solutions and cnoidal solitons. The modified F-expansion approach is an effective, powerful and straightforward method for obtaining the solitary wave solutions to the nonlinear partial differential equations (NPDEs). The effect of model parameters on the nature, properties and structures of the model solutions have been examined. It was noted that, the wave amplitude, bandwidths and phase shift are improved by changing model parameters in super periodic solitons and super periodic shocks. The new solutions obtained in this study may hold significance for the applications of electrostatic EASWs structures at critical density, which have been observed in diverse space plasma environments, including the plasma sheet boundary layers of the Earth’s magnetotail region for ions temperature ranging from 0.01 to 1 KeV.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"119 ","pages":"Pages 503-510"},"PeriodicalIF":6.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377057","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}