Optik最新文献

英文中文

Antibunching and sub-Poissonian photon statistics in degenerate frequency up-conversion process 简并频率上转换过程中的反聚束和亚泊松光子统计

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-04-01 Epub Date: 2026-01-07 DOI: 10.1016/j.ijleo.2026.172668

Rupesh Singh , Dilip Kumar Giri

The work is devoted to the antibunching and sub-Poissonian photon statistics in the degenerate frequency up-conversion (FUC) process using a short-time approximation in the Heisenberg picture. We analyse how pump photon numbers, interaction times, and coupling strengths affect nonclassicality, distinguishing between first- and second-order Hamiltonian interactions. Results show that first-order interactions lead to stronger nonclassical effects, though only second-order interactions enable antibunching in the harmonic mode due to higher-order pump contributions. Photon antibunching intensity increases with pump strength and shorter interaction times. In the first-order coupling interactions, the harmonic mode does not exhibit antibunching because a coherent or vacuum pump induces photon clustering. However, second-order interactions, where higher powers of the pump field contribute significantly, facilitate antibunching in the harmonic mode. Third-order antibunching exhibits the strongest nonclassical behaviour within the observed effects, followed by second- and first-order antibunching. It is more apparent that increased pump intensity and reduced interaction time both strengthen antibunching and sub-Poissonian photon statistics. While the pump mode exhibits clear antibunching, the harmonic mode displays milder nonclassicality. These results reveal the higher-order transitions of antibunching as an inherent quantum feature of light, valuable for quantum communication and single-photon sources with a probabilistic destination.

利用海森堡图像中的短时近似，研究了简并频率上转换（FUC）过程中的反聚束和亚泊松光子统计。我们分析了泵浦光子数、相互作用时间和耦合强度如何影响非经典性，区分了一阶和二阶哈密顿相互作用。结果表明，一阶相互作用导致更强的非经典效应，但由于高阶泵浦的贡献，只有二阶相互作用才能在谐波模式下实现反聚束。光子反聚束强度随泵浦强度和相互作用时间的缩短而增加。在一阶耦合相互作用中，谐波模式不表现出反聚束，因为相干或真空泵诱导光子聚簇。然而，二阶相互作用，其中高功率的泵浦场贡献显著，促进反聚束在谐波模式。在观察到的效应中，三阶反束表现出最强的非经典行为，其次是二阶和一阶反束。更明显的是，增加泵浦强度和减少相互作用时间都增强了反聚束和亚泊松光子统计。而泵浦模式表现出明显的反聚束，谐波模式表现出较温和的非经典性。这些结果揭示了反聚束的高阶跃迁作为光的固有量子特征，对量子通信和具有概率目的地的单光子源有价值。

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引用次数: 0

Evaluating short term financial marketing bitcoin prediction: A comparative analysis of large-kernel attention graph convolutional networks across various prediction horizon 评估短期金融营销比特币预测：跨不同预测范围的大核注意图卷积网络的比较分析

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-04-01 Epub Date: 2025-12-29 DOI: 10.1016/j.ijleo.2025.172663

Mohideen AbdulKader M , Sudhansu Sekhar Nanda , K. Sampath , D. Barani

One of the most popular investment assets nowadays is Bitcoin. The financial market volatility of bitcoin's price has drawn the attention of researchers and investors alike to the ways in which its price fluctuates. The paper proposes an evaluation of Short Term Financial Marketing Bitcoin Prediction: A Comparative Analysis of Large-Kernel Attention Graph Convolutional Networks across Various Prediction Horizons (BP-ST-LAGCN-NOA) for short-term Bitcoin market prediction. Then, pre-processed data are fed to the Large-kernel Attention Graph Convolutional Network (LAGCN) to effectively predict the bitcoin market in the short term. LAGCN does not express adaptive optimization strategies to determine optimal factors to effectively predict the Bitcoin market. Hence, the Nutcracker Optimization Algorithm (NOA) is employed to optimize the weight parameter of the Large-kernel Attention Graph Convolutional Network to predict the bitcoin market. Then the proposed BP-ST-LAGCN-NOA is implemented in Python, and the performance metrics like Accuracy, Precision, Recall, Specificity, F1-score, and ROC are analysed. The BP-ST-LAGCN-NOA model achieves 99.64 % accuracy, 99.21 % precision, 99.18 % recall, 98.14 % F1-Score and 98.47 % specificity, outperforming all baseline methods. The BP-ST-LAGCN-NOA model demonstrates superior accuracy and robustness in short-term Bitcoin market prediction, outperforming existing machine learning (ML) and deep learning (DL) approaches.

如今最受欢迎的投资资产之一是比特币。比特币价格在金融市场上的波动引起了研究人员和投资者对其价格波动方式的关注。本文提出了短期金融营销比特币预测的评价：跨不同预测视界的大核注意图卷积网络（BP-ST-LAGCN-NOA）对短期比特币市场预测的比较分析。然后，将预处理后的数据输入到大核注意图卷积网络（LAGCN）中，有效预测比特币短期市场走势。LAGCN没有表达自适应优化策略来确定最优因素，从而有效地预测比特币市场。因此，采用胡桃夹子优化算法（NOA）对大核注意图卷积网络的权重参数进行优化，预测比特币市场。然后用Python实现了BP-ST-LAGCN-NOA，并对准确率、精密度、召回率、特异性、F1-score和ROC等性能指标进行了分析。BP-ST-LAGCN-NOA模型准确率为99.64 %，精密度为99.21 %，召回率为99.18 %，F1-Score为98.14 %，特异性为98.47 %，优于所有基线方法。BP-ST-LAGCN-NOA模型在短期比特币市场预测中表现出卓越的准确性和鲁棒性，优于现有的机器学习（ML）和深度学习（DL）方法。

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引用次数: 0

Dual-parameter tunable high-Q optical response in 1D photonic crystals with Kerr-nonlinear graphene and polymer defect layers 具有克尔非线性石墨烯和聚合物缺陷层的一维光子晶体的双参数可调谐高q光响应

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-04-01 Epub Date: 2026-01-09 DOI: 10.1016/j.ijleo.2026.172670

Oumayma Habli , Jihene Zaghdoudi , Mounir Kanzari

This work numerically investigates the optical response of a one-dimensional photonic crystal incorporating a nonlinear defect layer based on either a polymer or graphene. Using the transfer matrix method, the influence of Kerr nonlinearity on the defect-mode transmission is analyzed under linear and nonlinear regimes. The results show that graphene exhibits a significantly stronger nonlinear response than the polymer defect layer, leading to enhanced wavelength tunability and higher spectral selectivity. A key contribution of this study is the demonstration of a dual-parameter tuning mechanism that combines input optical intensity and angle of incidence, enabling dynamic compensation between intensity-induced redshift and angle-induced blueshift of the defect mode. This dual control provides improved flexibility compared to conventional single-parameter approaches. The proposed graphene-based structure offers promising potential for tunable photonic devices such as optical filters, all-optical switches, sensors, and optical limiters.

本文研究了基于聚合物或石墨烯的非线性缺陷层的一维光子晶体的光学响应。利用传递矩阵法，分析了克尔非线性在线性和非线性条件下对缺陷模传输的影响。结果表明，石墨烯表现出比聚合物缺陷层更强的非线性响应，从而增强了波长可调性和更高的光谱选择性。本研究的一个关键贡献是展示了一种双参数调谐机制，该机制结合了输入光强度和入射角，实现了缺陷模式的强度诱导红移和角度诱导蓝移之间的动态补偿。与传统的单参数方法相比，这种双重控制提供了更高的灵活性。所提出的基于石墨烯的结构为光学滤波器、全光开关、传感器和光学限制器等可调谐光子器件提供了广阔的潜力。

引用次数: 0

Numerical and experimental characterization of whispering gallery modes in a microcylinder for displacement and force sensing 位移和力传感用微柱低语通道模态的数值和实验表征

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-11-20 DOI: 10.1016/j.ijleo.2025.172606

Mahdi Shayganmanesh, Mohammad Hossein Mahdieh, Reyhane Mokhtari

In this paper a microcylindrical resonator sensor was fabricated using PDMS polymer. The sensor works based on whispering gallery mode (WGM). The microcylinder filled with solution of Rhodamine 6B and glycerol. The Rhodamine was optically pumped by the second harmonics of a pulsed Nd:YAG laser beam and its emission provided WGM and resonance in microcylinder. The WGM spectra of microcylinder under applied forces were detected and analyzed by using a spectrophotometer. In addition to WGM spectra, optical images of the microcylinder under applied forces were taken using an appropriate optical set up and employing a CCD camera. The optical images show that any force on microcylinder side modifies its cross section from micro disk to micro elliptic. The experimental results show that such deformation in cross section leads to blue shift in WGM resonance wavelength. Using the geometrical data of images and a simple theory, the blue shifts due to force were estimated by calculations. The numerical results show good agreement with the experimental results.

本文采用PDMS聚合物制备了微圆柱谐振器传感器。该传感器基于窃窃廊模式（WGM）工作。微瓶中装满罗丹明6B和甘油溶液。利用脉冲Nd:YAG激光束的次谐波光泵浦罗丹明，其发射在微柱中产生WGM和共振。利用分光光度计对微柱在外力作用下的WGM光谱进行了检测和分析。除了WGM光谱外，还使用合适的光学装置和CCD相机拍摄了微柱在外力作用下的光学图像。光学图像表明，施加在微圆柱侧面的任何作用力都会使其横截面由微圆盘变为微椭圆。实验结果表明，这种截面变形导致WGM共振波长蓝移。利用图像的几何数据和一个简单的理论，通过计算估计了力引起的蓝移。数值计算结果与实验结果吻合较好。

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引用次数: 0

Securing iris image templates through ECC-based phase retrieval mask and multi-domain transforms integrated with chaotic umbrella mapping 基于相位检索掩模和混沌伞映射的多域变换对虹膜图像模板的保护

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-11-20 DOI: 10.1016/j.ijleo.2025.172605

Bhavana Sharma , Pankaj Rakheja , Hukum Singh , Mehak Khurana

The increasing demand of biometric technology in various applications highlights the important role of iris image templates encryption in ensuring robust image security safeguarding the confidentiality, legitimacy, and authenticity of iris images. This paper presents a novel encryption technique designed to improve security of iris image templates. The proposed technique combines elliptic curve cryptography (ECC), chaotic umbrella maps, and an uneven modulus decomposition (UMD) algorithm. The Gyrator and fractional Fourier domains are jointly leveraged for their non-linear transformation characteristics, enhancing encryption complexity. The Umbrella Map is incorporated along with phase masks produced by elliptic curve cryptography to strengthen the security. To add an extra layer of security, pixel scrambling is also introduced, enabling the conversion of iris input images into a one-channel encrypted output. MATLAB simulations and security tests were carried out, including statistical analysis, critical sensitivity assessments, and a look at possible threats. The outcomes demonstrate the scheme's resistance to statistical inspection, important sensitivity analysis, and noise attacks. The robust encryption method ensures protection against known, specific, and plaintext assaults.

生物识别技术在各种应用中的需求日益增长，这凸显了虹膜图像模板加密在确保鲁棒图像安全方面的重要作用，保障了虹膜图像的机密性、合法性和真实性。为了提高虹膜图像模板的安全性，提出了一种新的加密技术。该技术结合了椭圆曲线密码（ECC）、混沌保护伞映射和不均匀模分解（UMD）算法。旋转域和分数傅里叶域共同利用其非线性变换特性，提高了加密复杂度。伞形图与椭圆曲线密码术产生的相位掩模相结合，增强了安全性。为了增加额外的安全层，还引入了像素置乱，使虹膜输入图像转换为单通道加密输出。进行了MATLAB模拟和安全测试，包括统计分析、关键敏感性评估和对可能威胁的观察。结果表明，该方案具有抗统计检验、重要灵敏度分析和噪声攻击的能力。健壮的加密方法确保了对已知、特定和明文攻击的保护。

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引用次数: 0

An intelligent adaptive hybrid learning-based detection framework to evade DDoS attack for secure virtualized infrastructures in cloud computing environment 针对云计算环境下安全的虚拟化基础设施，提出了一种基于智能自适应混合学习的DDoS攻击检测框架

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-12-12 DOI: 10.1016/j.ijleo.2025.172641

Chinnala Balakrishna , Sanaboina Leela Krishna , Sridhar Mourya , B. Giridhar , Chaluvadi V. Raghavendran , Sudha Singaraju

“Cloud computing has transformed technology” with its unmatched scalability and ease of access, allowing users to leverage services under a flexible pay-as-you-go model. Distributed Denial of Service (DDoS) attacks hijack many distributed devices to overwhelm systems, making them a persistent cybersecurity concern. Although there are various detection methods already, the growing complexity and frequency of these threats demand more resilient and adaptive security solutions. Existing detection methods frequently fall short in effectively handling the dynamic nature of cloud environments. These limitations collectively motivate the development of more robust and integrated approaches. As a result, this study presents a new architecture for detecting DDoS attacks in virtual cloud computing systems using the Adaptive Hybrid Learning (AHyL) approach. Initially, datasets are collected from publicly available standard sources. Then, the gathered data undergoes data preprocessing to improve its quality. Subsequently, a Spatial Cross-Attention-based Fuzzy Autoencoder (SCA-FAE) is employed to extract robust features. The combination of Spatial Cross-Attention (SCA) and Fuzzy Autoencoder (FAE) in the SCA-FAE approach offers the distinctive advantage by leveraging spatial correlations and handling data uncertainty. These extracted features are forwarded to the AHyL model for the detection process. This offers the distinctive advantage of integrating an Extreme Learning Machine (ELM) with a Residual Recurrent Neural Network (Res-RNN) to balance high-speed processing. Prediction performance is further enhanced by optimizing the model’s parameters using the Random Number Updated Hippopotamus Optimization (RNU-HO) algorithm. Finally, a comparative evaluation shows that the proposed technique significantly outperforms traditional approaches.

“云计算已经改变了技术”，它具有无与伦比的可扩展性和易于访问性，允许用户在灵活的现收现付模式下利用服务。分布式拒绝服务（DDoS）攻击劫持了许多分布式设备，使系统不堪重负，使它们成为持久的网络安全问题。尽管已经有各种检测方法，但这些威胁的复杂性和频率不断增加，需要更具弹性和适应性的安全解决方案。现有的检测方法往往不能有效地处理云环境的动态性。这些限制共同促使开发更健壮和集成的方法。因此，本研究提出了一种新的架构，用于使用自适应混合学习（AHyL）方法检测虚拟云计算系统中的DDoS攻击。最初，数据集是从公开可用的标准来源收集的。然后对采集到的数据进行预处理，提高数据质量。随后，采用基于空间交叉注意的模糊自编码器（SCA-FAE）提取鲁棒特征。在SCA-FAE方法中，空间交叉注意（SCA）和模糊自编码器（FAE）的结合通过利用空间相关性和处理数据不确定性提供了独特的优势。这些提取的特征被转发到AHyL模型进行检测过程。这提供了将极限学习机（ELM）与残差递归神经网络（Res-RNN）集成以平衡高速处理的独特优势。通过使用随机数更新河马优化（RNU-HO）算法优化模型参数，进一步提高了预测性能。最后，对比评价表明，该方法明显优于传统方法。

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引用次数: 0

Propagation of vector solitons in waveguides with Helmholtz resonators: Transmission-line approach 亥姆霍兹谐振器波导中矢量孤子的传播：在线传输方法

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-12-09 DOI: 10.1016/j.ijleo.2025.172635

Souleymanou Abbagari , Alphonse Houwe , Lanre Akinyemi , Doka Yamigno Serge , Bouetou Thomas Bouetou

This paper investigates vector soliton interactions within an air-filled acoustic waveguide that is side-loaded with Helmholtz resonators and modeled as a transmission line incorporating nearest-neighbor coupling. Using a semi-discrete approximation, we derive coupled nonlinear Schrödinger equations that reveal how self-phase and cross-phase modulation depend on the normalized frequency. Analytical results indicate that only coupled bright-bright and dark-dark soliton interactions can propagate within the frequency bands supported by the resonator structure, while bright-dark and dark-bright soliton pairs are inhibited due to the influence of coupling strength. Modulation instability analysis highlights the role of nearest-neighbor coupling in altering the intensity and bandwidth of these solitons. Numerical simulations further demonstrate that the waveguide configuration supports the long-term evolution of wavenumbers, giving rise to rogue waves and periodic breathers under varying coupling conditions. Notably, the excitation of specific frequency bands allows for the emergence of Akhmediev breathers of types A and B during certain propagation intervals. In general, this study unveils novel wave dynamics introduced by incorporating nearest-neighbor coupling in acoustic waveguides with Helmholtz resonators.

本文研究了侧面加载亥姆霍兹谐振器的充气声波导中的矢量孤子相互作用，并将其建模为包含最近邻耦合的传输线。使用半离散近似，我们推导出耦合非线性Schrödinger方程，揭示了自相位和交叉相位调制如何依赖于归一化频率。分析结果表明，只有耦合的亮-亮和暗-暗孤子相互作用才能在谐振腔结构支持的频带内传播，而由于耦合强度的影响，亮-暗和暗-亮孤子对被抑制。调制不稳定性分析强调了最近邻耦合在改变这些孤子的强度和带宽中的作用。数值模拟进一步表明，波导结构支持波数的长期演变，在不同的耦合条件下产生异常波和周期性呼吸。值得注意的是，特定频段的激发允许在特定传播间隔内出现A型和B型艾哈迈耶夫呼吸器。总的来说，这项研究揭示了通过将声波波导中最近邻耦合与亥姆霍兹谐振器相结合而引入的新的波动动力学。

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引用次数: 0

Numerical investigation of one-soliton and two-soliton collision solutions in a nonlinear ferromagnetic equation 非线性铁磁方程中单孤子和双孤子碰撞解的数值研究

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-12-11 DOI: 10.1016/j.ijleo.2025.172639

Indira Sundaram , J. Sivapragasam , Sathishkumar Perumal

This study presents a numerical investigation of electromagnetic (EM) soliton propagation and collision phenomena in an anisotropic ferromagnetic medium characterized by higher-order nonlinearity and dispersion. The interaction between the magnetization of the medium and the magnetic field component of the EM wave is studied by solving Maxwell’s equations coupled with the Landau-Lifshitz (L-L) equation, which governs the magnetization dynamics. The resulting nonlinear magnetization behavior is described by a generalized derivative nonlinear Schrödinger (DNLS) equation, selected for its ability to capture complex spin interactions and electromagnetically induced nonlinear effects that are inadequately represented in conventional integrable models. To investigate the nonlinear spin excitations, we perform numerical simulations by solving the generalized DNLS equation using the Method of Lines, implemented in Mathematica software. This approach enables the identification of nonlinear spin excitations in the form of damped and amplitude-modulated one-soliton structures and phase-sensitive two-soliton collisions. Despite energy dissipation, the interactions retain spatial coherence, demonstrating the robustness of solitonic behavior under dispersive and nonlinear perturbations. Dispersion plays a critical role in modulating collision timing and shaping the post-interaction profiles. These findings advance the understanding of soliton robustness under perturbative conditions and provide valuable insights into nonlinear EM wave propagation with potential applications in magneto-optic switching and soliton-based waveguide technologies.

本文对具有高阶非线性和色散的各向异性铁磁介质中电磁孤子的传播和碰撞现象进行了数值研究。通过求解麦克斯韦方程组和控制磁化动力学的Landau-Lifshitz （L-L）方程，研究了介质磁化强度与电磁波磁场分量的相互作用。由此产生的非线性磁化行为由广义导数非线性Schrödinger （DNLS）方程描述，选择该方程是因为它能够捕获复杂的自旋相互作用和电磁感应非线性效应，这些效应在传统的可积模型中无法充分表示。为了研究非线性自旋激励，我们使用Mathematica软件实现的线法（Method of Lines）对广义DNLS方程进行了数值模拟。这种方法能够识别非线性自旋激励的阻尼和振幅调制的单孤子结构和相敏双孤子碰撞的形式。尽管能量耗散，相互作用仍然保持空间相干性，证明了在色散和非线性扰动下孤子行为的鲁棒性。色散在调制碰撞时间和形成相互作用后的轮廓中起着关键作用。这些发现促进了对微扰条件下孤子鲁棒性的理解，并为非线性电磁波传播提供了有价值的见解，具有在磁光开关和基于孤子的波导技术中的潜在应用。

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引用次数: 0

Electronic, transport and optical properties of a p-type transparent conductive oxides family A2B2O7 (A=Sn, Pb, B= Nb, Ta): A density functional theory study p型透明导电氧化物家族A2B2O7 （a =Sn, Pb， B= Nb, Ta）的电子、输运和光学性质：密度泛函理论研究

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-12-05 DOI: 10.1016/j.ijleo.2025.172634

Ting Yang , Wen-Guang Li , Zheng-Tang Liu , Qi-Jun Liu

Transparent conductive oxides (TCOs) are indispensable for next-generation optoelectronics, yet high-performance p-type TCOs remain scarce. In this theoretical study, we present a systematic density-functional-theory investigation of the cubic pyrochlore-structured oxides A₂B₂O₇ (A = Sn, Pb; B = Nb, Ta). All four compounds are predicted to be mechanically stable indirect-gap semiconductors. Using the ionization-energy-difference criterion combined with hybrid-HSE06 calculations, we identify Sn₂Nb₂O₇, Sn₂Ta₂O₇ and Pb₂Ta₂O₇ as promising intrinsic p-type conductors, with Sn₂Nb₂O₇ exhibiting the highest theoretical hole mobility (10.5 cm² V⁻¹ s⁻¹) and Sn₂Ta₂O₇ showing the lowest visible-light absorption. Our computational results provide quantitative design rules for pyrochlore-based p-type TCOs and point toward experimentally verifiable candidates for transparent electronics.

透明导电氧化物（tco）是下一代光电子技术不可或缺的材料，但高性能p型tco仍然稀缺。在这一理论研究中，我们提出了一个系统的密度泛函理论研究立方火石结构氧化物a₂B₂O₇（a = Sn, Pb; B = Nb, Ta）。预计这四种化合物都是机械稳定的间接间隙半导体。利用电离能差标准结合hybrid-HSE06计算，我们确定Sn₂Nb₂O₇、Sn₂Ta₂O₇和Pb₂Ta₂O₇是有潜力的本态p型导体，其中Sn₂Nb₂O₇的理论空穴迁移率最高（10.5 cm²V⁻¹s⁻¹），Sn₂Ta₂O₇的可见光吸收率最低。我们的计算结果为基于焦绿石的p型tco提供了定量设计规则，并指出了实验可验证的透明电子候选材料。

引用次数: 0

Heap Optimization Based Multi LSTM for enhancing maternal and fetal health monitoring through wearable devices 基于堆优化的多LSTM通过可穿戴设备增强母婴健康监测

IF 3.1 3区物理与天体物理 Q2 Engineering

Optik

Pub Date : 2026-03-01 Epub Date: 2025-11-26 DOI: 10.1016/j.ijleo.2025.172621

Rajkumar Ettiyan , V. Geetha

Monitoring maternal and fetal health is crucial due to risk such as gestational diabetes, hypertensive disorders, and fetal growth restrictions. Risk prediction with machine learning models and constant monitoring of vital signs using wearable devices is quite challenging. Because these model accuracy depends heavily on high quality unbiased data and lack of sufficient data can lead to unreliable results. To overcome these difficulties, Heap Optimization Based Multi LSTM was created to assess pregnancy risk and monitor fetal health. Initially, wearable sensors are implanted in the mother's body, transmitting necessary data to a mobile application. The Message Queuing Telemetry Transport protocol, is used for transmitting the data to cloud storage system for storing and predicting the health status of pregnant women and fetal. The collected data is pre-processed within cloud system using MIDA-based missing value imputation to ensure data integrity and slice adaptive normalization. The features are selected using Locally Linear Embedding to emphasize relevant aspects, followed by classification HO-MLSTM, which divides fetal health into three stages: normal, questionable, and pathological, and assigns pregnancy risk levels as low, medium, or high. The proposed method achieves 97.4 % fetal health and 94.5 % for maternal risk highlighting the effectiveness of the HO-MLSTM approach in minimizing maternal risk and enhancing fetal health. Consequently, these methods are highly suitable for wearable devices designed to accurately classify pregnancy risk levels and fetal health stages in pregnant women.

由于妊娠期糖尿病、高血压疾病和胎儿生长受限等风险，监测孕产妇和胎儿健康至关重要。使用机器学习模型进行风险预测和使用可穿戴设备持续监测生命体征是相当具有挑战性的。因为这些模型的准确性在很大程度上依赖于高质量的无偏数据，缺乏足够的数据会导致不可靠的结果。为了克服这些困难，建立了基于堆优化的多LSTM来评估妊娠风险和监测胎儿健康。最初，可穿戴传感器被植入母亲体内，将必要的数据传输到移动应用程序。消息队列遥测传输协议，用于将数据传输到云存储系统，用于存储和预测孕妇和胎儿的健康状况。采集到的数据在云系统内使用基于mida的缺失值插值进行预处理，保证数据的完整性和切片自适应归一化。使用局部线性嵌入来选择特征以强调相关方面，然后进行HO-MLSTM分类，将胎儿健康分为正常、可疑和病理三个阶段，并将妊娠风险等级划分为低、中、高。所提出的方法达到97.4% %的胎儿健康和94.5% %的孕产妇风险，突出了HO-MLSTM方法在最大限度地降低孕产妇风险和提高胎儿健康方面的有效性。因此，这些方法非常适用于设计用于准确分类孕妇妊娠风险水平和胎儿健康阶段的可穿戴设备。

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