Trajectory Tracking Nonlinear Hybrid Control of Automated Guided Vehicles by Antonio Sánchez-Rodríguez, Eduardo Bayona, J. Enrique Sierra-García, Matilde Santos

“…The stability of the controller is demonstrated for any differentiable trajectory. When a PID optimized with genetic algorithms is compared with the proposed controller for several trajectories, the LPC outperforms it in all cases.…”
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About designing a planned education system in an existing corporate infrastructure by D. T. Gedenidze, A. V. Sinitsyn

“…Despite the availability of solutions for corporate training on the market, developing your own system is still the optimal solution for a large company, allowing you to satisfy all the needs of employees and managers in managing corporate training, as well as the most optimal way to integrate the system into the existing over many years, the company’s technological infrastructure, while avoiding the involvement of thirdparty specialists.…”
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Environmental thresholds triggering changes in above and belowground biomass carbon in China by Xin Zhang, Shihang Zhang, Jun Zhou, Jianrong Fan

“…Quantifying the dynamics of above and belowground biomass carbon (AGBC and BGBC) is essential for optimizing carbon sink management. However, the environmental thresholds that govern these dynamics under climate change remain poorly understood in China. …”
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Minimal state-preparation times for silicon spin qubits by Christopher K. Long, Nicholas J. Mayhall, Sophia E. Economou, Edwin Barnes, Crispin H. W. Barnes, Frederico Martins, David R. M. Arvidsson-Shukur, Normann Mertig

“…Abstract Efficient preparation of quantum states on noisy intermediate-scale quantum processors remains a significant challenge to achieve quantum advantage. While gate-based methods have been the traditional approach, pulse-based algorithms offer promising alternatives with finer control and potentially reduced overheads. …”
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Infrared Small Target Detection Based on Double Gray-Values Descend Angle Contrast Measure by Song Guan, Dali Zhou, Xiaodong Wang, Pengji Zhou

“…Experimental evaluations were conducted on four publicly available datasets, comparing our proposed approach with seven existing algorithms. The results demonstrate that our method facilitates rapid detection of small targets affected by salt noise within complex backgrounds while exhibiting exceptional detection capabilities and real-time performance. …”
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A Comparative Study of Data-Driven Prognostic Approaches under Training Data Deficiency by Jinwoo Song, Seong Hee Cho, Seokgoo Kim, Jongwhoa Na, Joo-Ho Choi

“…In industrial system health management, prognostics play a crucial role in ensuring safety and enhancing system availability. While the data-driven approach is the most common for this purpose, they often face challenges due to insufficient training data. …”
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Enhancing Privacy in IoT-Enabled Digital Infrastructure: Evaluating Federated Learning for Intrusion and Fraud Detection by Amogh Deshmukh, Peplluis Esteva de la Rosa, Raul Villamarin Rodriguez, Sandeep Dasari

“…To mitigate this, solutions using federated averaging (FedAvg), federated proximal (FedProx), and federated optimization methods have been proposed. These methods work with data locality during training at local clients without exposing data, while maintaining global convergence to enhance the privacy of local models within the framework. …”
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Dynamic Monitoring and Precision Fertilization Decision System for Agricultural Soil Nutrients Using UAV Remote Sensing and GIS by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong

“…Real-time data processing algorithms enable rapid updates of soil nutrient status, while a time-series dynamic model captures seasonal variations and crop growth stage influences, improving prediction accuracy (RMSE reductions of 43–70% for nitrogen, phosphorus, and potassium compared to conventional laboratory-based methods and satellite NDVI approaches). …”
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FLIP: A Novel Feedback Learning-Based Intelligent Plugin Towards Accuracy Enhancement of Chinese OCR by Xinyue Tao, Yueyue Han, Yakai Jin, Yunzhi Wu

“…The plugin’s modular design enables seamless integration without requiring modifications to existing OCR algorithms, while its feedback mechanism adapts to domain-specific terminology and user preferences. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…Furthermore, their dependence on iterative optimization renders them unsuitable for large-scale real-time applications. …”
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Adaptive Multi-Scale Bayesian Framework for MFL Inspection of Steel Wire Ropes by Xiaoping Li, Yujie Sun, Xinyue Liu, Shaoxuan Zhang

“…Future work will focus on optimizing algorithmic efficiency and exploring transfer learning techniques for enhanced adaptability across different non-destructive testing (NDT) domains. …”
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Attention-enhanced StrongSORT for robust vehicle tracking in complex environments by Wei Xu, Xiaodong Du, Ruochen Li, Bingjie Li, Yuhu Jiao, Lei Xing

“…Abstract While multi-object tracking is critical for autonomous driving systems, traditional algorithms exhibit three fundamental limitations in complex scenarios: (1) blurred feature representation under occlusion and re-identification scenarios causing identity switches, (2) insufficient sensitivity to scale-variant targets due to fixed geometric constraints in conventional IoU-based loss functions, and (3) gradient degradation in deep convolutional layers hindering discriminative feature learning. …”
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Utilizing UAVs in Wireless Networks: Advantages, Challenges, Objectives, and Solution Methods by Mohammad Javad Sobouti, Amirhossein Mohajerzadeh, Haitham Y. Adarbah, Zahra Rahimi, Hamed Ahmadi

“…Additionally, we discuss the main methods and algorithms employed for UAV placement and trajectory optimization. …”
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Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Enhanced strategies for effective fruit picking using the Eye-in-Hand system involve the development of more dexterous robotic hands and improved algorithms for precisely predicting the optimal picking point of each fruit. …”
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A Review of Environmental Control Strategies and Models for Modern Agricultural Greenhouses by Shuailiang Chen, Aolong Liu, Fei Tang, Pei Hou, Yanli Lu, Pei Yuan

“…Greenhouse control involves regulating environmental parameters such as temperature, humidity, light, and CO₂ concentration to ensure an optimal growth environment for crops while conserving energy. …”
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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Energy-Efficiency Maximization in Backscatter Communication-Based Non-Orthogonal Multiple Access System: Dinkelbach and Successive Convex Approximation Approaches by Dingjia Lin, Tianqi Wang, Kaidi Wang, Zhiguo Ding

“…The goal is to maximize energy efficiency (EE) through the optimization of the beamforming matrix and the reflection coefficient of the BackCom devices. …”
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WaveConstLib: A java library for signal analysis and wavelet construction by Çağla Sarvan Cibil, Nalan Özkurt

“…It provides tools to create wavelet functions tailored to specific signals while adhering to WT conditions. Unlike traditional methods, WaveConstLib employs multi-objective evolutionary algorithms (MOEAs) optimization to construct signal-specific wavelet functions, ensuring superior adaptability and performance. …”
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IDLEWiSE by Chiara Fusar Bassini, Leonard Hackel, Thorren Kirschbaum

“…This paper outlines an optimization tool using efficient machine-learning algorithms like decision trees to learn optimal shutdown policies online. …”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…IoT-connected bins transmit data to a central server, which uses blockchain to ensure secure, transparent data storage. AI algorithms, including machine learning (ML) and deep learning (DL), classify waste in real-time, optimizing waste collection and recycling. …”
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