On the Combination of Harmonics and Polynoms in Econometric Modeling of RUB/AZN Exchange Rate by L. M. Mamedova

“…By breaking up the empirical analysis of given time series into time-scale polynomial and time-frequency components. Combinations of the optimal degree of variants of polynomials up to the 11th degree and the number of harmonics of sines and cosines of all possible discrete frequencies were revealed.Conclusion. …”
Get full text

River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…The RT-DETR, a member of the DETR family, has notably addressed the speed limitations of its predecessors by utilizing a high-performance hybrid encoder that optimizes query selection. Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. …”
Get full text

A probability integral method modified model for accurately characterizing subsidence at the boundary of a mining area by Bang Zhou, Shengcai Li, Jianrong Kang, Lu Zhang, Jinman Zhang, Ming Li

“…In response to this engineering issue, this paper analyzes the influence of PIM’s parameters change on the prediction results, based on which, the probability integral method modified model (PIM-MM) is established, the decreasing step fruit flies optimization algorithm (DS-FOA) used for parameters inversion is also proposed, which realizes the accurate subsidence prediction for the boundary of a mining area. …”
Get full text

Integrated Thermal Management Strategy Using High-Value Prioritized Experience Replay Deep Reinforcement Learning for Battery Electric Vehicles by Yongqiang Jia, Guanghui Cao, Jinrui Gao

“…In low-temperature environments, electric vehicles rely on effective thermal management strategies (TMS) to rapidly heat the battery to its optimal operating temperature while maintaining cabin temperature within a comfortable range. …”
Get full text

Robust Sandstorm Image Restoration via Adaptive Color Correction and Saturation Line Prior-Based Dust Removal by Shan Zhou, Fei Shi, Zhenhong Jia, Guoqiang Wang, Jian Huang

“…Enhancing the visibility of outdoor images under sandstorm conditions remains a significant challenge in computer vision due to the complex atmospheric interference caused by dust particles. While existing image enhancement algorithms perform well in mild sandstorm scenarios, they often struggle to produce satisfactory results in more severe conditions, where residual color casts and chromatic artifacts become pronounced. …”
Get full text

The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Classical keypoint matching methods find the extreme pose transitions between cameras present in a CVGL configuration challenging to operate in, while deep neural networks demonstrate superb capacity in this area. …”
Get full text

Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…For instance, understanding gas emissions from crops can help farmers optimize their activities, reducing fertilizer and pesticide use while improving yields. …”
Get full text

Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
Get full text

Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Our proposed MARL framework enables adaptive, decentralized decision-making for both the distribution system operator and individual VPPs, optimizing economic efficiency while maintaining grid stability. …”
Get full text

Synergistic Effect of <i>Bacillus</i> and Chitosan: From Flocculation to Enhanced Antimicrobial Activity by Selena Dmitrović, Nataša Lukić, Ivana Danilov, Vanja Vlajkov, Jovana Grahovac, Aleksandar Jokić

“…The response surface approach, followed by desirability function optimization and the genetic algorithm were applied. …”
Get full text

Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
Get full text

Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…A new hyperparameter optimization strategy is introduced to enhance clustering performance by tuning key parameters based on the silhouette index. …”
Get full text

Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
Get full text

Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Thus, the purpose of this study was to develop and optimize models by Cox regression and machine learning algorithms to predict the risk of aGVHD in which cyclosporin A exposure and common clinical factors were included as variables. …”
Get full text

Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix by Jitendra Singh, Aditya K. Jagannatham, Lajos Hanzo

“…Furthermore, to tackle the UM constraints in the sub-problem of the HTPC design, we propose a penalty-based Riemannian manifold optimization (PRMO) algorithm, which optimizes the HTPCs on the Riemannian manifold. …”
Get full text

Reinforcement Learning-Driven Secrecy Energy Efficiency Maximization in RIS-Enabled Communication Systems by Akram Y. Sarhan, Osamah A. Abdullah, Hayder Al-Hraishawi, Faisal S. Alsubaei

“…This study explores the use of physical layer security (PLS) to facilitate secure communications in RIS-assisted networks, tackling the important issues of safeguarding sensitive information while also addressing limited energy resources. This study examines the optimization of RIS passive beamforming, active beamforming, and power budgets with the aim of enhancing secrecy energy efficiency (SEE). …”
Get full text

An in-depth exploration of supervised and semi-supervised learning on face recognition by Purnawansyah, Wibawa Aji Prasetya, Widiyaningtyas Triyanna, Haviluddin, Darwis Herdianti, Azis Huzain

“…Although there are some instances of sub-optimal performance in certain algorithms like CNN on specific datasets, this research provides comprehensive insights into the effectiveness of various models in contexts of limited-label learning. …”
Get full text

EEG-Based Engagement Monitoring in Cognitive Games by Yusuf Ahmed, Martin Ferguson-Pell, Kim Adams, Adriana Ríos Rincón

“…They also completed the flow state scale for occupational tasks questionnaire after the easy, optimal, and hard levels of gameplay. Self-reported engagement scores significantly varied across the difficulty levels (<i>p</i> = 0.027), with the optimal level yielding the highest scores. …”
Get full text

Multi-Agent Deep Reinforcement Learning Cooperative Control Model for Autonomous Vehicle Merging into Platoon in Highway by Jiajia Chen, Bingqing Zhu, Mengyu Zhang, Xiang Ling, Xiaobo Ruan, Yifan Deng, Ning Guo

“…To enhance training efficiency, we develop a dual-layer multi-agent maximum Q-value proximal policy optimization (MAMQPPO) method, which extends the multi-agent PPO algorithm (a policy gradient method ensuring stable policy updates) by incorporating maximum Q-value action selection for platoon gap control and discrete command generation. …”
Get full text

Context-Adaptable Deployment of FastSLAM 2.0 on Graphic Processing Unit with Unknown Data Association by Jessica Giovagnola, Manuel Pegalajar Cuéllar, Diego Pedro Morales Santos

“…Simultaneous Localization and Mapping (SLAM) algorithms are crucial for enabling agents to estimate their position in unknown environments. …”
Get full text