alexandria engineering journal最新文献_第6页

The role of temporary architecture in the historical environment: Baghdad city/historic Saray axis—A case study 临时建筑在历史环境中的作用：巴格达市/萨拉伊历史轴线--案例研究

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-04 DOI: 10.1016/j.aej.2024.10.088

Mahmood Hussein Al-Musawi , Safaaaldeen Hussein Ali

Historical environments occur due to humans interacting with place and time. They are characterized by the presence of a variety of ancient architectural structures that reflect the history and culture of the place and that hold historical and cultural significance. These structures include buildings, historical sites, axes, and remnants of local architecture. Various methods have been employed to care for historical environments and preserve them. These include highlighting historical structures and their original details. Architects often adopt temporary architecture as an effective strategy to emphasize historical images and safeguard them from negative evolutionary trends. They work to present these images to the community periodically in different forms, attracting people to them. This research aims to construct a conceptual model of temporary architecture as a strategy for stimulation and experimentation and to enhance the historical environment. The model includes mechanisms and levels of temporary intervention in the historical environment. This conceptual framework was applied to the historical Saray axis in Baghdad, Iraq, to measure temporary interventions in projects designed by final-year architecture students. These interventions aimed to enhance the historical environment through the addition and restoration of missing parts using contemporary temporary structures. The research assumes that temporary architecture enhances the historical environment sustainably and periodically, enabling generations of architects to contribute effectively to showcasing their expertise in the historical environment. A case study methodology is adopted, using two case studies and the Delphi technique with three rounds, and statistical analysis is conducted to reveal the nature of temporary architecture and structures that enhance the historical environment and harmonize with the historical fabric of the Saray axis. From this research, we conclude that temporary architecture is important as a strategy for stimulation and experimentation in the historical environment, advocating for a blend of strategies to attract different behaviors to the historical surroundings.

历史环境是人类与地点和时间相互作用的产物。历史环境的特点是存在各种古代建筑结构，这些结构反映了当地的历史和文化，具有历史和文化意义。这些结构包括建筑物、历史遗址、斧头和当地建筑的遗迹。人们采用了各种方法来爱护和保护历史环境。其中包括突出历史建筑及其原始细节。建筑师通常采用临时建筑作为一种有效的策略，以强调历史形象并保护其免受负面演变趋势的影响。他们定期以不同的形式向社会展示这些形象，吸引人们前往参观。本研究旨在构建一个临时建筑的概念模型，将其作为一种刺激和实验策略，并提升历史环境。该模型包括对历史环境进行临时干预的机制和层次。这一概念框架被应用于伊拉克巴格达历史悠久的萨拉伊中轴线，以衡量由建筑专业毕业班学生设计的项目中的临时干预措施。这些干预措施旨在通过使用当代临时结构增加和修复缺失部分来改善历史环境。研究认为，临时建筑可以持续、定期地改善历史环境，使一代又一代的建筑师能够有效地在历史环境中展示他们的专业技能。研究采用了案例研究方法，使用了两个案例研究和三轮德尔菲技术，并进行了统计分析，以揭示提升历史环境并与萨拉伊中轴线历史结构相协调的临时建筑和结构的性质。通过这项研究，我们得出结论，临时建筑作为历史环境中的一种刺激和实验策略非常重要，主张融合各种策略，吸引不同的行为进入历史环境。

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引用次数: 0

An improved lightweight ConvNeXt for rice classification 用于水稻分类的改进型轻量级 ConvNeXt

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-02 DOI: 10.1016/j.aej.2024.10.098

Pengtao Lv , Heliang Xu , Qinghui Zhang , Lei Shi , Heng Li , Youyang Chen , Yana Zhang , Dengke Cao , Zhongyang Liu , Yixin Liu , Jingwen Han , Zhan Zhang , Yiran Qi

Under the pressure of climate change, the international food market is facing great uncertainty. Rice is widely grown as a major worldwide food crop, and different rice seeds often influence the future merit of a country's rice growth. As a major food crop widely grown around the world, the seed type of rice plays a key role in ensuring food security and optimizing agricultural productivity. Therefore, identifying the types of rice grains is an important task in rice breeding and cultivation. To this end, this study proposes a new model based on the ConvNeXt framework for detecting rice types, aiming to improve the identification efficiency. Our improved model achieved an average accuracy of 94.69 %. Compared to the baseline model ConvNeXt, the proposed network is more lightweight and more accurate. We conducted comprehensive experiments on the rice dataset from the GrainSpace public dataset to ensure the thoroughness and rigor of the study. Compared to existing models, our proposed model achieved the highest accuracy while maintaining lower FLOPs and parameters.

在气候变化的压力下，国际粮食市场正面临着巨大的不确定性。水稻是世界上广泛种植的主要粮食作物，不同的水稻种子往往影响着一个国家未来水稻生长的优劣。作为一种在全球广泛种植的主要粮食作物，水稻种子类型在确保粮食安全和优化农业生产力方面发挥着关键作用。因此，确定稻谷类型是水稻育种和栽培的一项重要任务。为此，本研究提出了一种基于 ConvNeXt 框架的水稻类型检测新模型，旨在提高识别效率。我们改进后的模型平均准确率达到 94.69%。与基线模型 ConvNeXt 相比，所提出的网络更轻便、更准确。我们在 GrainSpace 公共数据集中的水稻数据集上进行了全面的实验，以确保研究的全面性和严谨性。与现有模型相比，我们提出的模型在保持较低 FLOPs 和参数的同时，达到了最高的精确度。

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引用次数: 0

Melting ternary hybrid nanofluid stagnation point flow with velocity slip past a stretching/shrinking sheet: Numerical simulation and validation via P2SATRA 熔融三元混合纳米流体停滞点流动，速度滑过拉伸/收缩片：通过 P2SATRA 进行数值模拟和验证

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-02 DOI: 10.1016/j.aej.2024.10.082

Nur Syahirah Wahid , Nur Ezlin Zamri , Siti Zulaikha Mohd Jamaludin , Nur Hazirah Adilla Norzawary , Mohd Shareduwan Mohd Kasihmuddin , Mohd. Asyraf Mansor , Norihan Md Arifin , Ioan Pop

Ternary hybrid nanofluids are crucial to be modeled and researched before their commercial application as a heat transfer fluid. This study investigates the stagnation point flow of a ternary hybrid nanofluid past a stretching/shrinking sheet, focusing on the influence of the melting parameter and second-order velocity slip. The governing partial differential equations (PDEs) are initially formulated and subsequently reduced to ordinary differential equations (ODEs). These ODEs are further transformed into first-order form and numerically solved using the bvp4c solver in MATLAB. Stability analysis is conducted due to the existence of two potential solutions, of which only one proves stable upon analysis. The numerical results indicate significant enhancements in heat transfer performance under conditions of elevated melting and enhanced velocity slip. Reducing the melting parameter and second-order velocity slip may expand the solution range, leading to a delay in boundary layer separation. The stable numerical solution for the heat transfer rate is then validated with the use of a logic mining model namely Permutation 2 Satisfiability Reverse Analysis (P2SATRA). The most accurate induced logic, chosen to illustrate the overall relationship between the selected parameters is achieved in the third fold of a 10-fold cross-validation, yielding an accuracy of 0.81818.

在将三元混合纳米流体作为传热流体进行商业应用之前，对其进行建模和研究至关重要。本研究探讨了三元混合纳米流体经过拉伸/收缩薄片时的停滞点流动，重点研究了熔化参数和二阶速度滑移的影响。首先制定了控制偏微分方程 (PDE)，然后将其简化为常微分方程 (ODE)。这些 ODE 进一步转化为一阶形式，并使用 MATLAB 中的 bvp4c 求解器进行数值求解。由于存在两个潜在解，因此进行了稳定性分析，其中只有一个在分析后证明是稳定的。数值结果表明，在熔化程度升高和速度滑移增强的条件下，传热性能显著提高。降低熔化参数和二阶速度滑移可能会扩大解的范围，导致边界层分离延迟。然后，利用逻辑挖掘模型，即 Permutation 2 Satisfiability Reverse Analysis (P2SATRA)，对传热速率的稳定数值解进行了验证。在 10 倍交叉验证的第三倍中，选择了最准确的诱导逻辑来说明所选参数之间的整体关系，准确率为 0.81818。

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引用次数: 0

Sandpiper optimization with hybrid deep learning model for blockchain-assisted intrusion detection in iot environment 利用混合深度学习模型对区块链辅助的物联网环境入侵检测进行 Sandpiper 优化

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-01 DOI: 10.1016/j.aej.2024.10.032

Mimouna Abdullah Alkhonaini , Manal Abdullah Alohali , Mohammed Aljebreen , Majdy M. Eltahir , Meshari H. Alanazi , Ayman Yafoz , Raed Alsini , Alaa O. Khadidos

Intrusion detection in the Internet of Things (IoTs) is a vital unit of IoT safety. IoT devices face diverse kinds of attacks, and intrusion detection systems (IDSs) play a significant role in detecting and responding to these threats. A typical IDS solution can be utilized from the IoT networks for monitoring traffic, device behaviour, and system logs for signs of intrusion or abnormal movement. Deep learning (DL) approaches are exposed to promise in enhancing the accuracy and effectiveness of IDS for IoT devices. Blockchain (BC) aided intrusion detection from IoT platforms provides many benefits, including better data integrity, transparency, and resistance to tampering. This paper projects a novel sandpiper optimizer with hybrid deep learning-based intrusion detection (SPOHDL-ID) from the BC-assisted IoT platform. The key contribution of the SPOHDL-ID model is to accomplish security via the intrusion detection and classification process from the IoT platform. In this case, the BC technology can be used for a secure data-sharing process. In the presented SPOHDL-ID technique, the selection of features from the network traffic data takes place using the SPO model. Besides, the SPOHDL-ID technique employs the HDL model for intrusion detection, which involves the design of a convolutional neural network with a stacked autoencoder (CNN-SAE) model. The beetle search optimizer algorithm (BSOA) method is used for the hyperparameter tuning procedure to increase the recognition outcomes of the CNN-SAE technique. An extensive simulation outcome is created to exhibit a better solution to the SPOHDL-ID method. The experimental validation of the SPOHDL-ID method portrayed a superior accuracy value of 99.59 % and 99.54 % over recent techniques under the ToN-IoT and CICIDS-2017 datasets.

物联网（IoT）中的入侵检测是物联网安全的重要组成部分。物联网设备面临着各种各样的攻击，而入侵检测系统（IDS）在检测和应对这些威胁方面发挥着重要作用。典型的 IDS 解决方案可用于监控物联网网络的流量、设备行为和系统日志，以发现入侵或异常移动的迹象。深度学习（DL）方法有望提高物联网设备 IDS 的准确性和有效性。区块链（BC）辅助物联网平台的入侵检测有很多好处，包括更好的数据完整性、透明度和抗篡改性。本文从区块链辅助物联网平台出发，提出了一种新型鹬类优化器，该优化器具有基于混合深度学习的入侵检测功能（SPOHDL-ID）。SPOHDL-ID 模型的主要贡献在于通过物联网平台的入侵检测和分类过程实现安全性。在这种情况下，BC 技术可用于安全的数据共享过程。在所介绍的 SPOHDL-ID 技术中，使用 SPO 模型从网络流量数据中选择特征。此外，SPOHDL-ID 技术还采用了用于入侵检测的 HDL 模型，其中包括设计一个具有堆叠自动编码器（CNN-SAE）模型的卷积神经网络。在超参数调整过程中使用了甲虫搜索优化算法（BSOA）方法，以提高 CNN-SAE 技术的识别结果。为展示 SPOHDL-ID 方法的更好解决方案，创建了一个广泛的模拟结果。在 ToN-IoT 和 CICIDS-2017 数据集下，SPOHDL-ID 方法的实验验证结果表明其准确率分别达到 99.59 % 和 99.54 %，优于最新技术。

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引用次数: 0

Enhancing aviation control security through ADS-B injection detection using ensemble meta-learning models with Explainable AI 利用可解释人工智能的集合元学习模型，通过 ADS-B 喷射检测加强航空控制安全

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-11-01 DOI: 10.1016/j.aej.2024.10.042

Vajratiya Vajrobol , Geetika Jain Saxena , Sanjeev Singh , Amit Pundir , Brij B. Gupta , Akshat Gaurav , Kwok Tai Chui

The increasing use of Automatic Dependent Surveillance-Broadcast (ADS-B) technology in flight control systems has created many serious concerns.These weaknesses threaten the security and safety of our aviation industry. Therefore, to enhance aviation control security and better deal with these problems, this research focuses on developing a strong ADS-B injection detection system. It combines XGBoost and Random Forest with Logistic Regression in an Ensemble Learning Meta-Learning Model to identify ADS-B injection risks and categorise them. Ensemble methods, which combine several models can increase the detection accuracy and robustness of the model used to identify the threat. In addition, Explainable AI (XAI) methods are employed to enhance the process of explaining how the model reaches its decisions and building trust in aviation security systems. The system’s training, testing, and evaluation are conducted with ADS-B data. This result indicates that the Stacked Random Forest and XGBoost with Logistic Regression Meta-Learner with 99.60% accuracy, along with good recall rates (99.49%) and precision (99.41%). Also, aviation control authorities are reassured by the model’s transparent and applicable decision logic through the application of XAI techniques. This research contributes to enhanced aviation security by proposing a new, highly accurate ADS-B injection detection system with explainable outcomes. A strategy like this can help flight control systems maintain integrity amidst an ever-digitising aviation reality.

随着自动监控广播（ADS-B）技术在飞行控制系统中的应用越来越广泛，产生了许多严重的问题。因此，为了加强航空控制安全并更好地应对这些问题，本研究重点开发了一种强大的 ADS-B 注入检测系统。它将 XGBoost 和随机森林与逻辑回归结合在一个集合学习元学习模型中，以识别 ADS-B 注入风险并对其进行分类。结合多个模型的集合方法可以提高用于识别威胁的模型的检测准确性和鲁棒性。此外，还采用了可解释人工智能（XAI）方法，以加强解释模型如何做出决策的过程，并建立对航空安全系统的信任。该系统的培训、测试和评估是通过 ADS-B 数据进行的。结果表明，堆叠随机森林和 XGBoost 与逻辑回归元学习器的准确率为 99.60%，同时具有良好的召回率（99.49%）和精确率（99.41%）。此外，通过应用 XAI 技术，该模型的决策逻辑既透明又适用，让航空管制部门放心。这项研究提出了一种新型、高精度、结果可解释的 ADS-B 喷射检测系统，从而为加强航空安全做出了贡献。这样的策略有助于飞行控制系统在不断数字化的航空现实中保持完整性。

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引用次数: 0

Innovative design and experimental verification of cam shedding for high-speed looms 高速织机凸轮开口的创新设计和实验验证

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-10-31 DOI: 10.1016/j.aej.2024.10.096

Haifei Qiu , Ming Chen, Feiyang Li, Yifan Zhang

For overcoming space limitations and load-bearing defects of traditional conjugate cam shedding on looms, a novel cam shedding system with double-shaft was developed by incorporating mechanism analysis, theoretical calculations, modeling and simulation, and experimental verification. The lifting motion of the heald frame is controlled by the cosine acceleration law, with MATLAB compiling the reverse program of the cam theoretical profile. A functional digital prototype is created in ADAMS/View using planar rod groups, gear transmission, and conjugate cam mechanism. The simulation results of considering yarn tension exhibited highly consistent swing arm and heald frame motion curves with numerical calculations, and the dynamic performance of the shedding system is affected by yarn tension, which leads to an increase in motor torque and acceleration oscillation in the low-frequency domain. Furthermore, an experimental proportional model was produced using 3D printing technology and tested for motion performance at varying rotational speeds, verifying the design's theoretical accuracy and practical feasibility, indicating that this mechanism runs smoothly and reliably in lifting and returning the heald frame by cam; meanwhile, the yarn deformation and shed characteristics are apparent, meeting the requirements of the shedding weaving process of plain fabric. The work in this paper effectively solves the problem of contact wear between the cam and rotor, which is conducive to design innovation and performance improvement of the conjugate cam shedding on high-speed looms.

为克服传统织机共轭凸轮开口的空间限制和承重缺陷，通过机理分析、理论计算、建模仿真和实验验证，开发了一种新型双轴凸轮开口系统。综框的升降运动由余弦加速度定律控制，MATLAB 编制了凸轮理论轮廓的反向程序。利用平面杆组、齿轮传动和共轭凸轮机构，在 ADAMS/View 中创建了功能数字原型。考虑到纱线张力的仿真结果表明，摆臂和综框运动曲线与数值计算结果高度一致，而且脱纱系统的动态性能受到纱线张力的影响，导致电机扭矩增加和低频域加速度振荡。此外，利用三维打印技术制作了实验比例模型，并测试了不同转速下的运动性能，验证了设计的理论准确性和实际可行性，表明该机构在通过凸轮提升和返回综框时运行平稳可靠，同时纱线变形和脱落特征明显，满足平纹织物脱落织造工艺的要求。本文的研究工作有效解决了凸轮与转子之间的接触磨损问题，有利于高速织机共轭凸轮开口装置的设计创新和性能提升。

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引用次数: 0

An effective computational approach to the local fractional low-pass electrical transmission lines model 局部分数低通输电线模型的有效计算方法

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-10-31 DOI: 10.1016/j.aej.2024.07.021

Kang-Jia Wang

In this research, a new fractional low-pass electrical transmission lines model (LPETLM) described by the local fractional derivative (LFD) is derived for the first time. By defining the Mittag-Leffler function (MLF) on the Cantor set (CS), two special functions, namely, the

L T_{δ}

-function and

L C_{δ}

-function, are extracted to develop an auxiliary function, which is employed to look for the non-differentiable (ND) exact solutions (ESs) together with Yang’s non-differentiable transformation. Eight sets of the ESs are obtained and the corresponding dynamic performances on the CS for

γ = \ln 2 / \ln 3

are displayed. As expected, for

γ \to 1

, the ESs of the local fractional LPETLM become the ESs of the classic LPETLM and the outlines are also depicted graphically. The outcomes confirm that our new method is a promising tool to handle the local fractional PDEs in the electrical and electronic engineering.

本研究首次推导出一种用局部分数导数（LFD）描述的新分数低通输电线模型（LPETLM）。通过定义 Cantor 集（CS）上的 Mittag-Leffler 函数（MLF），提取出两个特殊函数，即 LTδ 函数和 LCδ 函数，从而建立了一个辅助函数，并利用该函数和杨氏无差异变换寻找无差异精确解（ES）。得到了八组 ES，并显示了 γ=ln2/ln3 时 CS 上相应的动态性能。不出所料，当γ→1 时，局部分数 LPETLM 的 ES 变成了经典 LPETLM 的 ES，其轮廓也用图形表示出来。这些结果证明，我们的新方法是处理电子电气工程中局部分式 PDE 的一种有前途的工具。

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引用次数: 0

A deep learning ICDNET architecture for efficient classification of histopathological cancer cells using Gaussian noise images 利用高斯噪声图像对组织病理学癌细胞进行高效分类的深度学习 ICDNET 架构

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-10-31 DOI: 10.1016/j.aej.2024.10.081

Hui Zong , Wenlong An , Xin Chen , Zhanhui Yang , Heng Zhou , Xiangchao Liu , Jianchu Lin , Chuanyue Zong

Histopathology image classification is crucial in pathological diagnosis workflow for early detection and treatment. The integration of deep learning technology has greatly improved diagnostic accuracy and efficiency. However, there are limitations when morphological features are not obvious in pathological sections, leading to difficulties in identifying deep cells and an increased risk of misdiagnosis. To address this issue, this study introduces a new hybrid network model, termed ICDNET, designed to fuse global and local features without destroying the integrity of the feature data, thus enhancing the accuracy of medical image classification. The ICDNET model consists of two main features: (i) a serial hierarchical structure composed of global and local feature blocks; and (ii) an Internal Communication Hierarchical Fusion Block (ICHF) and an Efficient Dual Self-Attention (EDA) mechanism. This network structure solves internal communication issues and enriches contextual semantic information, extracting local features and global representations from different internal spaces. To evaluate the performance of the ICDNET network model, experiments were conducted on four major public datasets with the addition of Gaussian noise. The experimental results demonstrate excellent accuracy and the ability to handle limited training samples, highlighting the potential of the ICDNET model to assist pathologists in pathological diagnosis.

在病理诊断工作流程中，组织病理学图像分类对于早期发现和治疗至关重要。深度学习技术的融入大大提高了诊断的准确性和效率。然而，当病理切片的形态特征不明显时，就会出现局限性，导致难以识别深部细胞，增加误诊风险。针对这一问题，本研究引入了一种新的混合网络模型，称为 ICDNET，旨在融合全局和局部特征，同时不破坏特征数据的完整性，从而提高医学影像分类的准确性。ICDNET 模型由两个主要特征组成：(i) 由全局和局部特征块组成的串行分层结构；(ii) 内部通信分层融合块（ICHF）和高效双自注意（EDA）机制。这种网络结构解决了内部通信问题，丰富了上下文语义信息，从不同的内部空间提取了局部特征和全局表征。为了评估 ICDNET 网络模型的性能，我们在四个主要的公共数据集上进行了实验，并添加了高斯噪声。实验结果表明，ICDNET 网络模型具有极高的准确性和处理有限训练样本的能力，凸显了该模型协助病理学家进行病理诊断的潜力。

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引用次数: 0

A highly sensitive fluorescent detection method utilizing B and S co-doped graphene quantum dots for ibuprofen analysis 利用 B 和 S 共掺杂石墨烯量子点分析布洛芬的高灵敏度荧光检测方法

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-10-31 DOI: 10.1016/j.aej.2024.10.089

Zheyi Geng

A highly sensitive and selective fluorescent probe utilizing B and S co-doped graphene quantum dots (BS-GQDs) has been created for detecting ibuprofen. The co-doping strategy effectively modulated the electronic structure and surface properties of GQDs, resulting in enhanced fluorescence quantum yield and sensing performance. The BS-GQDs exhibited strong fluorescence quenching upon interaction with ibuprofen, which was attributed to the formation of a ground-state complex and electron transfer from BS-GQDs to ibuprofen. Under optimal conditions, the sensor exhibited a broad linear range, a low detection limit, and outstanding selectivity for ibuprofen compared to other common medications and interferents. The practical utility of the sensor was validated through the successful identification of ibuprofen in spiked urine and serum samples, achieving high recovery rates and accuracy. The BS-GQDs-based fluorescent sensor provides a promising platform for sensitive, rapid, and reliable monitoring of ibuprofen in pharmaceutical and biomedical fields.

利用 B 和 S 共掺杂石墨烯量子点（BS-GQDs）创建了一种用于检测布洛芬的高灵敏度和选择性荧光探针。共掺杂策略有效地调节了石墨烯量子点的电子结构和表面特性，从而提高了荧光量子产率和传感性能。BS-GQDs 与布洛芬相互作用时表现出强烈的荧光淬灭，这归因于基态复合物的形成以及 BS-GQDs 与布洛芬之间的电子转移。在最佳条件下，该传感器的线性范围宽、检测限低，与其他常见药物和干扰物相比，对布洛芬具有出色的选择性。通过对尿液和血清样品中布洛芬的成功鉴定，验证了该传感器的实用性，实现了高回收率和高准确度。基于 BS-GQDs 的荧光传感器为在制药和生物医学领域灵敏、快速、可靠地监测布洛芬提供了一个前景广阔的平台。

引用次数: 0

Computational analysis for fractional model of coupled Whitham-Broer-Kaup equation Whitham-Broer-Kaup 耦合方程分数模型的计算分析

IF 6.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

alexandria engineering journal

Pub Date : 2024-10-30 DOI: 10.1016/j.aej.2024.09.061

Jagdev Singh , Arpita Gupta , Dumitru Baleanu

In this research paper, we study a semi analytical technique to solve the nonlinear partial differential equations. This technique is good combination of homotopy analysis method with Kharrat-Toma transform. Also, we present the numerical solution of nonlinear fractional coupled Whitham-Broer-Kaup equation using studied technique. The Whitham-Broer-Kaup model is broadly considered to study the tsunami wave dynamics under gravity. The regularized version of Hilfer-Prabhakar fractional derivative is used to model the problem. Some qualitative properties, existence and uniqueness of the considered model and its solution are also discussed.The obtained solutions are presented graphically to show the efficiency of studied technique. Error analysis tables are also given to demonstrate the accuracy of obtained results.

在本研究论文中，我们研究了一种求解非线性偏微分方程的半解析技术。该技术是同调分析方法与 Kharrat-Toma 变换的良好结合。此外，我们还介绍了利用所研究的技术对非线性分数耦合 Whitham-Broer-Kaup 方程进行数值求解的方法。Whitham-Broer-Kaup 模型被广泛用于研究重力作用下的海啸波动力学。使用正则化版本的 Hilfer-Prabhakar 分数导数对该问题进行建模。此外，还讨论了所考虑模型的一些定性属性、存在性和唯一性及其求解。还给出了误差分析表，以证明所获结果的准确性。

引用次数: 0