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A machine learning approach to address robust bi-objective gate assignment under aircraft's taxi delay uncertainties

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Expert systems with Applications 2025年 285卷

作者： Shadman, Majid Kordani, Ali Abdi Akbaripour, Hossein Imam Khomeini International University Faculty of Technical and Engineering Qazvin Iran Amirkabir University of Technology Faculty of Industrial Engineering and Management Systems Tehran Iran

Although gate assignment may appear to be a relatively straightforward process, it represents a significant challenge due to the inherent uncertainties. Despite the extensive research conducted on the gate assignment, its uncertainty aspects have not been subjected to more realistic robustness approach and the utilization of modern forecasting methods. Indeed, the main problem of this study, find the method to solve gate assignment problem with a taxi time prediction approach with considering uncertain parameters. This research aims to optimize gate assignment by considering uncertainties and deploying machine learning approach, with the goal of increasing operational efficiency and improving passenger experiences. Despite the absence of concerted efforts to integrate machine learning methodologies for taxi time prediction with taxi delay-based gate assignment, this research endeavored to combine the above with robust optimization using a polyhedral approach, which represents a significant innovation over previous work. A mathematical multiobjective model comprising uncertain parameters was constructed and three machine learning algorithms were employed to estimate taxi times. Subsequently, a set-induced robust counterpart with polyhedral approach was created. With the case study that is performed on the Phoenix airport, strong correlation was observed between the actual and predicted taxi times/lengths based on statistical analysis. The results obtained from the mathematical programming output demonstrated favorable outcomes in the context of uncertainty, thereby facilitating the optimization of gate assignment with respect to taxi delay while maintaining a conservative approach. The results exhibit implementation of robust optimization enables airport authorities to effectively manage gate assignment within acceptable confidence interval. © 2025

关键词： Learning algorithms

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Air Pollutant Prediction Using Shallow Architecture Machine Learning Algorithms 8th

Air Pollutant Prediction Using Shallow Architecture Machine ...

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8th World Conference on Smart Trends in systems Security and Sustainability, WorldS4 2024

作者： Olaifa, Moses Malele, Vusumuzi Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria South Africa Unit of Data Science and Computing Vaal Campus North-West University Vanderbijlpark South Africa

ISBN: (纸本)9789819786947

Over the past few decades, mortality rates associated with air quality pollution have risen in numerous countries around the globe. This pollution stems from different factors such as meteorological conditions, human activities from urban industrialization, vehicular emission, and so on. Air pollution constituents such as NO2, CO, SO, and coarse and fine particulate matter for different locations have been analyzed to learn both correlation and inter-dependency for long and short terms. However, many of these studies overlook datasets collected using low-cost tools and equipment. Most of the time, datasets of this nature are marred with inconsistencies and gaps at irregular intervals. This may render the air pollutant data unsuitable. In order to test the suitability of machine learning algorithms on such dataset, this study conducts a time-series forecast analysis using the prophet algorithm. Two additional models including linear regressor and random forest regressor are trained and tested on the same dataset and a comparative analysis of the three models is performed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Drone-Based Public Surveillance Using 3D Point Clouds and Neuro-Fuzzy Classifier

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Computers, Materials & Continua 2025年第3期82卷 4759-4776页

作者： Yawar Abbas Aisha Ahmed Alarfaj Ebtisam Abdullah Alabdulqader Asaad Algarni Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Science and Engineering College of InformaticsKorea UniversitySeoul02841Republic of Korea Cognitive Systems Lab University of BremenBremen28359Germany

Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot ***,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera *** research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)*** first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale *** YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further *** joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are *** features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity ***-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing *** particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.

关键词： Activity recognition geodesic distance pattern recognition neuro fuzzy classifier

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Investigating carbide characteristics effect on multiscale mechanical behavior of AISI 420 steel using crystal plasticity simulation

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Journal of Materials Research and technology 2025年 36卷 10487-10506页

作者： Kegu Lu Yadong Zhou Soheil Solhjoo Maysam Naghinejad Redmer van Tijum Yutao Pei Jan Post Advanced Production Engineering Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 3 9747 AG the Netherlands Engineering Systems and Design Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen Nijenborgh 4 9747 AG the Netherlands

Understanding the impact of precipitates on the mechanical behavior of material is crucial for effective material design and application. This research focuses on AISI 420 stainless steel, characterized by a ferritic matrix with dispersed carbides in its annealed state. This study employs a multiphase crystal plasticity (CP) model to systematically investigate the influence of variations in carbide characteristics, including their fraction at grain boundaries (GBs), number, average size, and volume fraction, on multiscale mechanical behavior. The workflow includes generating representative volume elements (RVEs) from the microstructure of the as-received AISI 420 steel, calibrating constitutive parameters within the CP model, and validating the CP-RVE model against experimental textures and mechanical properties. A novel method is introduced to capture anisotropic behavior by accurately replicating the experimental approach. Subsequently, diverse RVEs are generated by modifying carbide characteristics to evaluate their impact on stress-strain curves, anisotropic behavior, and micromechanical interactions, while preserving the characteristics of ferrites. The results are compared with experiments and theoretical insights. The findings reveal that an increase in either the fraction of carbides at GBs or the carbide volume fraction enhances the steel's strength. Empirical equations are derived to predict these effects on mechanical properties efficiently. Moreover, increasing the carbide volume fraction leads to more inhomogeneous strain and stress distributions in both carbides and ferrites, while reducing anisotropy (Lankford coefficient). This study highlights the potential of the CP-RVE model as a tool for exploring macroscale behavior and studying the influence of microstructural features.

关键词： Carbide AISI 420 steel Crystal plasticity Multiscale mechanical behavior

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Impact of EV charging strategies on solar-powered residential buildings: unidirectional vs. bidirectional charging in Jordan

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Discover Sustainability 2025年第1期6卷 1-16页

作者： Al-Amayreh, Malik Alamayreh, Ahmad Amer, Amal A. Alternative Energy Technology Department Faculty of Engineering and Technology Al-Zaytoonah University of Jordan P.O. Box 130 Amman 11733 Jordan Department of Intelligent Robotics Systems Engineering American University of Madaba Amman Jordan Data Science and Artificial Intelligence Department Al-Ahliyya Amman University Amman Jordan

Unidirectional chargers, valued for their simplicity and cost-effectiveness, are widely deployed. In contrast, bidirectional chargers enable advanced functionalities such as Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) but come with greater complexity, higher costs, and design challenges. This aim of this research is to analyze unidirectional and bidirectional charging systems integrated with renewable energy, from both economic and environmental perspectives. Additionally, the research conducts a technical analysis of different EV charging technologies via Polysun software, considering a predefined mobility profile that includes charging times and kilometers driven. The study focuses on households with renewable energy systems connected to the grid, evaluating energy consumption, grid reliance, CO₂ emissions, and financial viability across scenarios with varying numbers of EVs (1–3) over one year. While bidirectional EV setups enhance self-consumption and reduce dependence on the external grid, they face financial challenges, including higher initial costs and a lower net present value (NPV) due to maintenance expenses. In Jordan the time-of-use (TOU) pricing system has applied for EVs charging. This study reveals that the bidirectional EV charging improves energy efficiency and reduces CO₂ emissions by optimizing PV energy utilization in Jordan to charge EVs, however, its increased initial costs under TOU pricing highlight the need for supportive policies to encourage wider adoption. © The Author(s) 2025.

关键词： Bidirectional charging CO₂ emissions in EV charging Solar-powered EV charging Time of use pricing Unidirectional charging

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The interplay between histone modifications and nuclear lamina in genome regulation

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Journal of Genetics and Genomics 2025年第1期52卷 24-38页

作者： Chang Sun Yanjing Zhao Liping Guo Juhui Qiu Qin Peng Institute of Systems and Physical Biology Shenzhen Bay LaboratoryShenzhen 518132China Faculty of Medicine and Health Sciences Barcelona UniversityBarcelonaSpain Division of Life Science Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina School of Biology and Biological Engineering South China University of TechnologyGuangzhouGuangdong 510006China Key Laboratory for Biorheological Science and Technology of Ministry of Education State and Local Joint Engineering Laboratory for Vascular ImplantsCollege of BioengineeringChongqing UniversityChongqing 400030China

Gene expression is regulated by chromatin architecture and epigenetic remodeling in cell homeostasis and *** modifications act as the key factors to modulate the chromatin *** histone modifications are strongly associated with the localization of *** primarily localizes at the nuclear periphery,where it interacts with lamina proteins to suppress gene *** this review,we summarize the potential bridges that have regulatory functions of histone modifications in chromatin organization and transcriptional regulation at the nuclear *** use lamina-associated domains(LADs)as examples to elucidate the biological roles of the interactions between histone modifications and nuclear lamina in cell differentiation and *** the end,we highlight the technologies that are currently used to identify and visualize histone modifications and LADs,which could provide spatiotemporal information for understanding their regulatory functions in gene expression and discovering new targets for diseases.

关键词： Histone modifications Chromatin organization Nuclear lamina Lamina-associated domain Genome regulation Cell differentiation

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Microdroplet splitting and mixing by portable triboelectric nanogenerator

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Nano Research 2025年第2期18卷 741-750页

作者： Qi Gao Qin Xiang Wenkai Liu Mengru Ding Wei Long Jianlong Wang Xiaojun Cheng Hengyu Li Zhong Lin Wang Tinghai Cheng Guangzhou Institute of Blue Energy Knowledge CityHuangpu DistrictGuangzhou 510555China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of SciencesBeijing 101400China Faculty of Mechanical and Electrical Engineering Kunming University of Science and TechnologyKunming 650500China

Theadvancementofdigital microfluidics technology has been pivotal in academic research andengineering ***,the prevailing limitation is that traditional voltage sources generate an excess of Joule heat,adversely impacting droplet ***,the power supply equipment required by digital microfluidics limits its ***,we propose a self-powered microdroplet manipulation(SMDM)via triboelectric nanogenerator(TENG),which presents a capability for spliting and mixing different kinds of ***,SMDM is based on the electroosmotic flow principle,thereby enabling droplet spliting in the range of from 2 to 630μ***,for droplet spliting in the range of from 5 to 60μL,the TENG only requires a power output ranging from 2.704 to 6.084 *** addition,SMDM demonstrates proficiency in droplet mixing,which achieves complete mixing of 10μL droplets in 60 s and 30μL droplets in a mere 53 ***,leveraging the strengths of the TENG,a self-powered microdroplet manipulated system is designed for digital *** carries significant advantages over the traditional voltage source,including self-powered,low-Joule heat,increased safety and enhanced *** research provides a new solution for portable applications of digital microfluidics.

关键词： triboelectric nanogenerator microdroplet manipulation digital microfluidics droplet splitting droplet mixing

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Complex Emotion Estimation using Analysis-by-Synthesis of Facial Expression Images

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IEEE Access 2025年 13卷 88731-88746页

作者： Khine, Win Shwe Sin Siritanawan, Prarinya Kotani, Kazunori Japan Advanced Institute of Science and Technology School of Information Science Japan Shinshu University Informatics and Interdisciplinary Systems Division Graduate School of Science and Technology Department of Engineering Nagano Japan Kanazawa University Faculty of Transdisciplinary Science Institute of Philosophy in Interdisciplinary Science Ishikawa Japan

This research proposes an approach for recognizing facial expressions for complex emotion estimation through the utilization of generated facial images. The proposed approach consists of two main parts: facial image generation and facial expression recognition. In the first part, we introduce Conditioned Emotion Generative Adversarial Networks (cEmoGANs) to synthesize images that convey complex facial expressions. Unlike previous methods, our generative model maintains face identity information and expresses various types of complex emotions. This capability encourages the generator to have control over the image generation process, resulting in enhanced image quality, reduced distortion, and increased diversity of generated images. The second part involves the design of a multiple-label classification based on a convolutional neural network trained on the complex facial expression images generated from the first part, which is employed in the recognition of complex facial expressions for emotion estimation. Our model, using images generated by cEmoGANs, demonstrates a notable performance surpassing the capabilities of the previous models in comparative evaluations. © 2013 IEEE.

关键词： Convolutional neural networks

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Optimal Design and Tuning of TID Power System Stabilizer for Multi-machine Power System Using Dandelion Optimizer

Optimal Design and Tuning of TID Power System Stabilizer for...

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International Conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2024

作者： Hattabi, Intissar Kheldoun, Aissa Bradai, Rafik Khettab, Soufian SET Laboratory Blida 1 University Faculty of Technology Electrical and Control Department Blida Algeria Laboratory of Signals and Systems Institute of Electrical and Electronic Engineering University M’hamed Bougara Boumerdes35000 Algeria LATSI Blida 1 University Faculty of Technology Electronics Department Blida09000 Algeria

ISBN: (纸本)9783031803000

In this study, we explore the enhancement of stability in a four-machine power system through the optimized tuning of Tilt-Integral-Derivative Power System Stabilizer (TID-PSS) parameters. We introduce a novel application of the Dandelion Optimizer (DO) algorithm, designed to provide robust damping and stability under fault conditions. To improve the effectiveness of the DO algorithm, we compare its performance with several established optimization techniques, including Particle Swarm Optimization (PSO), HGS (Hunger Games Search), HBA (Honey Badger Algorithm), EO (Equilibrium Optimizer), and AVOA (African Vulture Optimization algorithm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Particle swarm optimization (PSO)

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GENSIMO - A Generic Framework for Modelling Social Insurance systems 25th

GENSIMO - A Generic Framework for Modelling Social Insuranc...

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25th International Workshop on Multi-Agent-Based Simulation, MABS 2024

作者： de Haan, Fjalar J. Thompson, Jason School of Computing and Information Systems Faculty of Engineering and Information Technology The University of Melbourne Parkville Australia Melbourne Centre for Data Science The University of Melbourne Parkville Australia Department of Psychiatry Faculty of Medicine Dentistry and Health Sciences The University of Melbourne Parkville Australia

ISBN: (纸本)9783031880162

We report on the design, development and prototype testing of gensimo (GENeric Social Insurance MOdeling), a free and open-source software framework for modelling and simulation of social insurance systems. We discuss the conceptual and software design considerations of the framework in general before demonstrating how it works in detail by setting it up to model a particular social insurance scheme. We then present how we used this prototype set up to model the impact of a policy intervention on the workload of the insurer. While gensimo is under active development and we are a while away from serious verification and validation, this prototype testing shows realistic results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Software testing

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