Stability of optical knots in atmospheric turbulence by D. G. Pires, D. Tsvetkov, H. Barati Sedeh, N. Chandra, N. M. Litchinitser

“…Additionally, we propose an optimization algorithm to maximize the distance between the phase singularities at each longitudinal plane, facilitating measurements of optical knots and improving their performance in the presence of turbulence.…”
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Variational Quantum Simulation: A Case Study for Understanding Warm Starts by Ricard Puig, Marc Drudis, Supanut Thanasilp, Zoë Holmes

“…While our main focus is on this case study of variational quantum simulation, we end by discussing how our results work in other iterative settings.…”
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Swarm Robot Exploration Strategy for Path Formation Tasks Inspired by Physarum polycephalum by Yandong Luo, Jianwen Guo, Zhenpeng Lao, Shaohui Zhang, Xiaohui Yan

“…For the research of swarm robotics, our algorithm not only can lead multirobot as a whole to overcome the limitations of very simple individual agents but also can offer better performance in terms of search efficiency and success rate. …”
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Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…Current industry practices often approximate mildly curved surfaces with flat plates within tolerances, but optimizing this substitution to minimize fitting errors while reducing the quantity of curved plates remains a critical engineering challenge. …”
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Flexible hardware for teaching and research in renewable energy and off-grid microgrids by Cristian Escudero-Quintero, Juan Pablo Guzman-Rodriguez, Juan Pablo Villegas-Ceballos, Elkin Edilberto Henao-Bravo, Daniel Gonzalez-Montoya

“…Microgrids are an active research field due to their integration of renewable and non-renewable energy sources alongside energy storage systems to supply both DC and AC loads. While existing studies extensively explore hierarchical control structures, focusing on algorithm design and optimization, practical implementation remains challenging due to system complexity. …”
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A Gain-Computation Enhancements Resource Allocation for Heterogeneous Service Flows in IEEE 802.16 m Mobile Networks by Wafa Ben Hassen, Meriem Afif

“…This method has a crucial role in the resource management and optimization. In a single service access, we propose a dynamic resource allocation algorithm at the physical layer aiming to maximize the cell data rate while ensuring fairness among users. …”
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Hierarchical energy management of distribution network with multi-microgrids based on double Stackelberg game by XIE Yuanhao, LIN Shenghong, ZHU Jianquan

“…In the external game, the distribution network as leader sets the prices, while microgrids as followers adjust their trading strategy with the distribution network. …”
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Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning by Sangwoo Park, Osvaldo Simeone

“…Quantum machine learning is a promising programming paradigm for the optimization of quantum algorithms in the current era of noisy intermediate-scale quantum computers. …”
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Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…The proposed method ultimately provides a computationally efficient and robust intelligent monitoring solution for agricultural mechanization, facilitating the transition from conventional agricultural practices toward sustainable, low-carbon production paradigms through algorithmic optimization.…”
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Detection of child depression using machine learning methods. by Umme Marzia Haque, Enamul Kabir, Rasheda Khanam

“…<h4>Background</h4>Mental health problems, such as depression in children have far-reaching negative effects on child, family and society as whole. It is necessary to identify the reasons that contribute to this mental illness. …”
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End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment by Cong Wang, Valerio Mariani, Frédéric Poitevin, Matthew Avaylon, Jana Thayer

“…We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. …”
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Towards Robust Speech Models: Mitigating Backdoor Attacks via Audio Signal Enhancement and Fine-Pruning Techniques by Heyan Sun, Qi Zhong, Minfeng Qi, Uno Fang, Guoyi Shi, Sanshuai Cui

“…Second, we apply an adaptive fine-pruning algorithm to selectively deactivate malicious neurons while preserving the model’s linguistic capabilities. …”
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Multi-Feature Long Short-Term Memory Facial Recognition for Real-Time Automated Drowsiness Observation of Automobile Drivers with Raspberry Pi 4 by Michael Julius R. Moredo, James Dion S. Celino, Joseph Bryan G. Ibarra

“…The model was trained on the NTHU-DDD dataset and optimized using long short-term memory (LSTM) deep learning algorithms implemented using TensorFlow version 2.14.0. …”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…We describe a docking method based on stochastic global minimization of funnel-shaped energy functions in the space of rigid body motions (SE(3)) while accounting for flexibility of the interface side chains. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. …”
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Coal mining equipment lifecycle management system architecture and key technology by Yihui PANG, Jinglong BI, Pengzhe YUAN, Baofu ZHAO, Ziwei DING

“…An optimization algorithm and software platform for comprehensive mining equipment selection were developed, and a method for constructing a series spectrum and coding system for coal mining equipment was proposed. …”
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A Novel Smart Molecular Fuzzy Decision Support System for Solid-State Battery Investments in Grid-Level Renewable Energy Storage by Gang Kou, Hasan Dincer, Serhat Yuksel, Edanur Ergun, Serkan Eti

“…For this purpose, a new decision-making model is developed that includes expert weighting with the entropy game, evaluation balancing with the Q-learning algorithm, calculation of criterion weights with the least squares optimization (LSO) and alternative ranking with the molecular ranking (MORAN) method. …”
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Deep learning-based energy efficient LSFD weights prediction for user centric cell free massive MIMO system by Moustafa Mohamed, Salwa El-Ramly, Bassant Abdelhamid

“…These models are trained using dataset generated from heuristic sparse LSFD optimization algorithm, this allows the models to learn the sparsity nature of the system and apply AP-UE association based on the values of the predicted LSFD weights at the receiver side while using the large scale fading coefficients as the models’ input. …”
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Distributed RL-Based Resource Allocation and Task Offloading for Vehicular Edge of Things Computing by Ghada Afifi, Bassem Mokhtar

“…We formulate a belief-based optimization problem to maximize the QoE of vehicular users while providing performance guarantees that account for geospatial uncertainty associated with the availability of embedded resources. …”
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Faster Convergence With Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning Over Wireless Networks by Daniel Perez Herrera, Zheng Chen, Erik G. Larsson

“…Decentralized stochastic gradient descent (D-SGD) is a widely adopted optimization algorithm for decentralized training of machine learning models across networked agents. …”
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