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Individual mapping and asymmetric dual supervision for discrete cross-modal hashing

EXPERT SYSTEMS WITH APPLICATIONS 2024年 247卷

作者： Wang, Song Zhao, Huan Zhang, Zixing Li, Keqin Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China Key Lab Embedded & Network Comp Hunan Prov Changsha 410082 Peoples R China SUNY Coll New Paltz Dept Comp Sci New Paltz NY 12561 USA

Cross -modal hashing has gained popularity in similarity search due to its excellent query efficiency and economical storage costs. However, current models frequently overlook the distinctive property of each modality, resulting in reduced accuracy due to inadequate utilization of these attributes. Moreover, there is a weak semantic relevance between modality attributes and multiple supervision knowledge (the labels and similarity constraints constructed by labels), accompanied by a cumulative quantization of the models. To address these issues, we propose an Individual Mapping and Asymmetric Dual Supervision method (IMADS). It merges specific and shared information to effectively learn a cross -modal representation space. Furthermore, we present an asymmetric dual supervision learning framework to produce discriminative hash codes. This framework achieves two primary goals: (1) Combing cross -modal representation and multiple supervision information to enhance the consistent relation of distinct modalities, and (2) developing a discretea* optimization algorithm to mitigate the information loss caused by the hash code. Comprehensive experimental results illustrate that the introduced IMADS outperforms other stat-of-the-art hashing methods.

关键词： Asymmetric dual supervision Cross-modal hashing Individual mapping optimization algorithm

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Artificial Intelligence in Geopolymer Concrete Mix Design: A Comprehensive Review of Techniques and Applications

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Iranian Journal of Science and Technology - Transactions of Civil Engineering 2025年 1-33页

作者： Mushthofa, Malik Thedy, John Teguh, Mochamad Purwanto Pratama, Adjie Gemilang Han, Ay Lie Department of Civil Engineering Islamic University of Indonesia Yogyakarta 55584 Indonesia Department of Bioenvironmental Systems Engineering National Taiwan University Taipei 10617 Taiwan Department of Civil Engineering Diponegoro University Semarang 50275 Indonesia

This systematic review explores the application of Artificial Intelligence (AI) in optimizing the mix design of fly ash-based geopolymer concrete (FABGC). Analyzing studies published between 2014 and 2025, it examines key methodologies, including machine learning models,a* optimization algorithms, and multi-criteria decision-making approaches. Critical aspects such as data preprocessing, AI model selection, hyperparameter tuning, explainable AI (XAI), and optimization strategies are synthesized to provide a comprehensive perspective on AI-driven FABGC research. The review identifies Deep Residual Networks (ResNet) and Extreme Gradient Boosting (XGB) as the most accurate models for predicting FABGC strength, consistently outperforming others due to their lower error metrics. Backpropagation Neural Networks (BPNN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) also demonstrate competitive performance, while Random Forest (RF) and Decision Tree (DT) models excel in computational efficiency with shorter training times. Despite being the most widely implemented, Artificial Neural Networks (ANN) rarely achieve the highest predictive accuracy. Traditional regression methods, though straightforward, lag behind in performance. These findings underscore the need for standardized datasets, enhanced collaboration, and innovative AI-driven approaches to improve FABGC mix design optimization. Addressing these challenges will facilitate more reliable and efficient AI applications in sustainable concrete technology. © The Author(s), under exclusive licence to Shiraz University 2025.

关键词： Artificial intelligence Fly ash Geopolymer concrete Mix design optimization algorithm

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Aerodynamic Shape optimization for Delaying Dynamic Stall of Airfoils Using Cokriging Regression

Aerodynamic Shape Optimization for Delaying Dynamic Stall of...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech Forum)

作者： Raul, Vishal Leifsson, Leifur Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

ISBN: (数字)9781624106095

ISBN: (纸本)9781624106095

The dynamic stall phenomenon produces adverse aerodynamic loading, which negatively affects the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides a practical approach for delaying and mitigating dynamic stall characteristics without the addition of an auxiliary system. A typical ASO investigation requires multiple evaluations of accurate but time-consuming computational fluid dynamics (CFD) simulations. In the case of dynamic stall, unsteady CFD simulations are required for airfoil shape evaluation;combining it with high-dimensions of airfoil shape parameterization renders the ASO investigation computationally costly. In this study, metamodel-based optimization (MBO) is proposed using the multifidelity modeling (MFM) technique to efficiently conduct ASO investigation for computationally expensive dynamic stall cases. MFM methods combine data from accurate high-fidelity (HF) simulations and fast low-fidelity (LF) simulations to provide accurate and fast predictions. In particular, Cokriging regression is used for approximating the objective and constraint functions. The airfoil shape is parameterized using six PARSEC parameters. The objective and constraint functions are evaluated for a sinusoidally oscillating airfoil with the unsteady Reynolds-averaged Navier-Stokes equations at a Reynolds number of 135,000, Mach number of 0.1, and reduced frequency of 0.05. The initial metamodel is generated using 220 LF and 20 HF samples. The metamodel is then sequentially refined using the expected improvement infill criteria and validated with the normalized root mean square error. The refined metamodel is utilized for finding the optimal design. The optimal airfoil shape shows higher thickness, larger leading-edge radius, and an aft camber compared to baseline (NACA 0012). The optimal shape delays the dynamic stall occurrence by 3 degrees and reduces the peak aerodynamic coefficients. The performance of the MFM method is also co

关键词： Aerodynamic Shape optimization NACA 0012 Computational Fluid Dynamics Reynolds Averaged Navier Stokes Airfoil Geometry Leading Edges Lift Coefficient Richardson Extrapolation Vortices optimization algorithm

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Adaptive mutant particle swarm optimization based precise cargo airdrop of unmanned aerial vehicles

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APPLIED SOFT COMPUTING 2022年 130卷

作者： Zhang, An Xu, Han Bi, Wenhao Xu, Shuangfei Northwestern Polytech Univ Sch Aeronaut Xian 710072 Peoples R China

Emerging unmanned system technologies and smart logistics have motivated logistics enterprises to use unmanned aerial vehicles (UAVs) for last-mile cargo delivery through the air so as to benefit from its flexibility and low cost. It is useful to deliver cargoes by airdrops from fixed-wing UAVs. However, wind and parameter errors of the UAV could make the cargo deviate from the desired landing point. To improve the accuracy of airdrop methods, this paper presents the Continuously Computed Release Point under conditions of strong wind (SW-CCRP) airdrop strategy to transport the cargo to a given position by a fixed-wing UAV. In this strategy, a set of differential equations are used to model the cargo motion and wind perturbations are considered. Based on the established motion model and the kinematic relationships between the cargo and the target position, the expected release point can be accurately predicted in real time. In order to satisfy the precision requirement, the precision assignment is studied to determine the permissible parameter error ranges. In view of that the conventional precision assignment methods are difficult to be applied in the airdrop system because of its complexity and strong nonlinearity, an adaptive mutant particle swarm optimization (AMPSO) algorithm is proposed to solve this problem, in which the adaptive inertia weight can balance the global and local search. In addition, the mutation factor of the AMPSO is able to avoid premature convergence and stagnation. Finally, two specific test scenarios are designed to validate the effectiveness of the proposed approaches.

关键词： Smart logistics Fixed-wing UAV Precision airdrop Adaptive mutant particle swarm optimization algorithm Precision assignment

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A newa* optimization algorithm for the design of aperiodic multilayer mirror for 17.1 nm and 30.4 nm

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OPTOELECTRONICS AND ADVANCED MATERIALS-RAPID COMMUNICATIONS 2013年第3-4期7卷 167-172页

作者： Zhu, Huaxin Gao, Jinsong Wang, Tongtong Zhao, Jingli Liu, Guilin Li, Shuai Jiangnan Univ Sch Sci Wuxi 214122 Jiangsu Peoples R China Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Key Lab Opt Syst Adv Mfg Technol Changchun 130033 Peoples R China

A new algorithm, Genetic/Tabu hybrid algorithm (GTHA) to optimize the aperiodic multilayer mirrors which combines the advantages of genetic algorithm (GAs) with tabu search (TS) algorithm is proposed in the extreme ultraviolet (EUV) range. Aperiodic multilayers are designed using GTHA for the selection of Fe-IX and He-II emission lines contrasting to the traditional periodic multilayers for a single wavelength. Materials of Mo and Si are selected for their high stability and fairly high reflectivity. High reflectance of 48.62% for the Fe-IX line (lambda=17.1nm) and reflectance of 20.57% for the He-II line (lambda=30.4nm) are reached by the new algorithm. Comparisons between aperiodic multilayers found by GTHA and the ones optimized using GAs indicate the effectiveness and reliability of the new hybrid algorithm. The aperiodic designs are compared with the periodic ones as well. And the aperiodic multilayers found by GTHA also have the better performance than periodic ones. The practicability of the aperiodic design optimized by GHTA is verified by the sensitivity analyses to thicknesses errors, which indicated it more feasible to fabricate the aperiodic multilayers in practice.

关键词： Optical thin Elm optimization algorithm Aperiodic multilayers

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Mitigating Cyber Anomalies in Virtual Power Plants Using Artificial-Neural-Network-Based Secondary Control with a Federated Learning-Trust Adaptation

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ENERGIES 2024年第3期17卷 619页

作者： Taheri, Seyed Iman Davoodi, Mohammadreza Ali, Mohd Hasan Univ Memphis Dept Elect & Comp Engn Memphis TN 38152 USA

Virtual power plants (VPPs) are susceptible to cyber anomalies due to their extensive communication layer. FL-trust, an improved federated learning (FL) approach, has been recently introduced as a mitigation system for cyber-attacks. However, current FL-trust enhancements, relying solely on proportional-integral (PI), exhibit drawbacks like sensitivity to controller gain fluctuations and a slow response to sudden disturbances, and conventional FL-trust is not directly applicable to the non-independent and identically distributed (non-IID) datasets common in VPPs. To address these limitations, we introduce an artificial neural network (ANN)-based technique to adapt FL-trust to non-IID datasets. The ANN is designed as an intelligent anomaly mitigation control method, employing a dynamic recurrent neural network with exogenous inputs. We consider the effects of the most common VPP attacks, poisoning attacks, on the distributed cooperative controller at the secondary control level. The ANN is trained offline and tested online in the simulated VPP. Using MATLAB simulations on a HOMER-modeled VPP, the proposed technique demonstrates its superior ability to sustain normal VPP operation amidst cyber anomalies, outperforming a PI-based mitigation system in accuracy and detection speed.

关键词： virtual power plant federated learning optimization algorithm power system distributed generation artificial neural network

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An algorithm to optimize the optical sensor design for tip clearance and tip timing measurements 7

An algorithm to optimize the optical sensor design for tip c...

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Conference on Optical Sensing and Detection VII Part of SPIE Photonics Europe Conference

作者： Zubia, Gorka Amorebieta, Josu Zubia, Joseba Durana, Gaizka Univ Basque Country Dept Commun Engn Plaza Ingeniero Torres Quevedo 1 E-48013 Bilbao Basque Country Spain

ISBN: (纸本)9781510651555;9781510651548

In this work, an algorithm for the optimization of the design of an optical fiber bundle displacement sensor for Tip Clearance and Tip Timing measurements is presented. The former is based on the gaussian beam mathematical approach, and implements a fiber arrangement comprised of a transmitting single-mode fiber and two concentric rings of receiving multimode fibers. The software includes a graphical user interface that allows modifying relevant geometrical parameters of the sensor and fiber characteristics, and enables monitoring in real time the effects of such modifications. Results indicate that in order to achieve the most sensitive design with the largest operating range, the key parameters are the gain configuration, the distance between the receiving fiber rings and the radii of receiving fibers, and that the best fitting sensor configuration is a tradeoff among the aforementioned characteristics as it is heavily dependent on the measurement constraints. The results obtained by the simulation tool were validated in good agreement with the calibration curve of the manufactured optical fiber bundle displacement sensor in a scaled rotor.

关键词： optical fiber sensor optimization algorithm tip clearance tip timing aircraft turbines displacement measurement

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Comparison of Electrified Aircraft Propulsion Drive Systems with Different Electric Motor Topologies

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JOURNAL OF PROPULSION AND POWER 2021年第5期37卷 733-747页

作者： Sirimanna, Samith Thanatheepan, Balachandran Lee, Dongsu Agrawal, Shivang Yu, Yangxue Wang, Yuyao Anderson, Aaron Banerjee, Arijit Haran, Kiruba Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Urbana IL 61801 USA Hitet LLC Champaign IL USA

Y Electric aircraft propulsion is a growing research area that looks into achieving propulsion through fully electric or hybrid electric systems while achieving low CO2 emissions. The system-level benefit gained by different electric and hybrid-electric propulsion schemes depends heavily on the performance of system-level components in the electric drive-train, including the electric motor, gear box, motor drive, protection systems, as well as the thermal management system. When comparing motor topologies, it is important to understand performance measures such as efficiency and specific power on a drive system level. Many different motor types have been qualitatively compared and can be found in the literature. To guide appropriate component selection, this paper presents details of a quantitative study for a given electric propulsion drive system. A Pareto optimal front for a notional drive system of a 1.5 MW electrical propulsor with different motor types is generated and compared. Ana* optimization algorithm coupled with an electromagnetic finite element analysis software tool was used to optimize the induction motor, switched reluctance motor, wound rotor synchronous motor, permanent magnet synchronous motor (PMSM), slotless PMSM, permanent-magnet-assisted synchronous reluctance motor, brushless DC motor, and brushless doubly fed reluctance motor types for efficiency and specific power. Overall advantages considering system-level efficiency, specific power, and a few other key metrics such as origin of losses, cooling complexity, manufacturing tolerance, and fault tolerance are discussed. This gives an indication of the relative performance of different motor types and confirms the overall advantage of PM motor topologies in aircraft propulsion.

关键词： Aircraft Propulsion System Switched Reluctance Motor Finite Element Analysis Electric Propulsion optimization algorithm Thermal Management System Fault Tolerance Software Tool Hybrid Electric Aircraft Torque Ripple

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Aeroacoustic and aerodynamic optimization of propeller blades

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Chinese Journal of Aeronautics 2020年第3期33卷 826-839页

作者： Peixun YU Jiahui PENG Junqiang BAI Xiao HAN Xiang SONG School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an 710072China

It is of great significance to develop a high-efficiency and low-noise propeller optimization method for new-generation propeller aircraft *** with free form deformation method,dynamic mesh interpolation technology,optimization algorithm,surrogate model,aerodynamic calculation and aeroacoustic prediction model module,the integrated aerodynamic and aeroacoustic design method of propeller is *** optimization design for the six-blade propeller is carried *** non-reduction in efficiency,thrust coefficient and the minimum of aerodynamic noise is treated as the optimization design *** spatial vorticity distribution of the propeller before and after the design is also analyzed by using unsteady computational fluid dynamics *** results show that the optimized propeller can effectively reduce the aerodynamic noise *** maximum total sound pressure level can be reduced by 5 dB without reducing its aerodynamic *** developed method has good application potential in low-noise optimization design of propeller and other rotating machinery.

关键词： Aeroacoustic Aerodynamic Dynamic mesh interpolation technology Free form deformation method optimization algorithm Propeller Sound pressure level Surrogate model

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Comprehensive exploration: Automatic mode-locking technology and its multidisciplinary applications

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INFRARED PHYSICS & TECHNOLOGY 2024年 138卷

作者： Liu, He Sun, Chenxi Zhang, Haoran Harbin Univ Sci & Technol Sch Measurement & Commun Engn Harbin Peoples R China

We present a thorough review of the evolution and current status of automatic mode -locking technology, offering insights into its remarkable developments. Automatic mode -locking technology commences with traversal algorithms and genetic algorithms, progressing to machine learning. The advancements ofa* optimization algorithms have ushered in a new era characterized by exceptional time efficiency, enhanced precision, adaptability to multiple variables, and the ability to engage with complex mode -locking regimes. This review concentrates on the improvements of hardware components of automatic mode -locking technology in addition to these algorithmic advances. We introduce the evolution of pivotal components, including polarization control elements and central control sections, which play a critical role in achieving stability and integration, and introduction of realtime measurement techniques in hardware, such as the time -stretched dispersive Fourier transform, which accurate monitoring and adjustment of clamping status and optical characteristics. Finally, a summary and outlook on the development of automatic mode -locking technology is presented.

关键词： Automatic mode -locking optimization algorithm Time -stretched dispersive Fourier transform

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