Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques by Daniel Amigo, David Sánchez Pedroche, Jesús García, José Manuel Molina, Jekaterina Trofimova, Emmanuel Voet, Benoît Van Bogaert

“…We introduce four key improvements: (1) a novel segmentation algorithm for more precise flight phase identification, (2) an improved invalid height detection process using LOWESS and sliding window analysis, (3) a protection mechanism against simultaneous measurements at the Kalman filter level, and (4) an optimized approach for smooth overshoot correction during segment transitions. …”
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Method of Diagnostics of Operation Modes of Individual Heat Supply Units, Allowing to Detect Pre-Emergency Situations at an Early Stage by Dvortsevoy A.I., Borush O.V., Khoreva V.A., Yakovina I.N.

“…This was confirmed by the "Elbow Method", which determined the optimal number, which made it possible to significantly improve the forecasting of emergency modes. …”
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Evaluating the performance and feasibility of integrating thermoelectric generators with solar photovoltaic panels: A case study by D Lakshmi Satya Nagasri, ram kumar Alajingi, Ponnambalam Pathipooranam, S. Senthil raja, Mohd Faiz bin Mohd Salleh, R. Marimuthu

“…Further, a conclusion is drawn from the techno-economic analysis to focus on optimizing the number of TEGs placed under SPV and improving MPPT algorithms to enhance performance and reduce costs.…”
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Securing fruit trees future: AI-driven early warning and predictive systems for abiotic stress in changing climate by Muhammad Ahtasham Mushtaq, Muhammad Ateeq, Muhammad Ikram, Shariq Mahmood Alam, Muhammad Mohsin Kaleem, Muhammad Atiq Ashraf, Muhammad Asim, Khalid F. Almutairi, Mahmoud F. Seleiman, Fareeha Shireen

“…Specifically, multi-omics, data accessibility, algorithmic biases, the cost of implementation and requirements for robust training programs need to integrate for sustainable agriculture. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…By utilizing its powerful nonlinear mapping ability and adaptive learning characteristics, the accuracy of blood glucose concentration prediction is effectively improved. The research results indicate that this method has the advantages of noninvasiveness, convenience, and low cost, but it also faces technical challenges such as individual differences and environmental interference.…”
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IMAGE SEGMENTATION AND OBJECT SELECTION BASED ON MULTI-THRESHOLD PROCESSING by Vladimir Yu. Volkov, Oleg A. Markelov, Mikhail I. Bogachev

“…Although this is achieved at the cost of the resource-consuming multi-threshold analysis procedure for each processed image, this can be also partially compensated by the simplicity of the algorithm and its possible parallel implementation.…”
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Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…The methodology integrates the tunable-Q wavelet transform (TQWT) for signal decomposition, optimizing Q-factor parameters to extract precise features, and morphological component analysis (MCA) with the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) for effective component separation. …”
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A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards by Yaning Zhai, Ling Zhang, Xin Hu, Fanghu Yang, Yang Huang

“…To address these challenges, this paper proposes a multi-object fruit tracking and counting method, which integrates an improved YOLO-based object detection algorithm with a dynamically optimized Kalman filter. …”
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Mapping individual tree crowns to extract morphological attributes in urban areas using unmanned aerial vehicle-based LiDAR and RGB data by Geonung Park, Bonggeun Song, Kyunghun Park

“…Using ML-based approaches, we conducted object-based image analysis to optimize the use of the WS algorithm because applying WS directly to urban environments, as in forests, overestimated the ITC size by 151.37 %. …”
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DEVELOPMENT OF A GRAVITATIONAL AND PENDULUM SOLAR TRACKER FOR STANDALONE PHOTOVOLTAIC PANELS by Jorge A. Wissmann, Carlos E. C. Nogueira, Marcelo M. M. Zampiva, Jair A. C. Siqueira, Doglas Bassegio

“…A tracking prototype was developed whose structure is classified as chronological due to its fixed rotation, manual as it requires daily adjustment, single-axis azimuthal, and "analog" as it lacks motors, sensors, or algorithms. The results showed that the developed tracking prototype achieved a 9.69% energy production increase during the research period, with peaks of 35.51% on sunny days, and a significant efficiency improvement during the early morning and late afternoon. …”
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study by Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

“…Finally, the accuracy and efficiency of the classification model were improved by optimizing the combination of base learners. …”
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Flexible Combinatorial-Bids-Based Auction for Cooperative Target Assignment of Unmanned Aerial Vehicles by Tianning Wang, Zhu Wang, Wei Li, Chao Liu

“…A comparison of the results demonstrates that the FCBA can provide comparable optimal results to a genetic algorithm but has better computational efficiency, and the reconnaissance effectiveness can be improved by considering cooperative observation.…”
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On the Choice of System Strength Metrics for the Allocation and Sizing of Synchronous Condensers in Power Grids by Shereefdeen Oladapo Sanni, Olatunji Obalowu Mohammed, Suprava Chakraborty, Ayodele Isqeel Abdullateef, Abdulrahaman Okino Otuoze, Olumoroti Ikotun, Ephraim Bonah Agyekum

“…Although the NRSCR-based method significantly improved system performance during faults—offering faster voltage recovery post-fault and higher fault current contributions—it resulted in a cost increase of approximately 7 times. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…The results underscore the potential of ML models to significantly enhance prediction accuracy over a wide data range, reduce computational costs, and improve the efficiency of CCUS operations. …”
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Damage prediction of rear plate in Whipple shields based on machine learning method by Chenyang Wu, Xiangbiao Liao, Lvtan Chen, Xiaowei Chen

“…The results demonstrate that the training and prediction accuracies using the Random Forest (RF) algorithm significantly surpass those using Artificial Neural Networks (ANNs) and Support Vector Machine (SVM). …”
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. by André G Coimbra, Cleiane G Oliveira, Matheus P Libório, Hasheem Mannan, Laercio I Santos, Elisa Fusco, Marcos F S V D'Angelo

“…The application of these techniques aims to improve the quality of life for individuals, reduce healthcare costs, and allocate available resources more efficiently, making it a preventive action.…”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…The usage of the device can also beneficial to the intelligent maintenance of electrical cabinets and optimize maintenance costs.…”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…The study considers the creation of ensembles combining different Convolutional Neural Network (CNN) models and transformer architectures to understand whether different optimization algorithms can result in more robust and efficient classification across various plankton datasets. …”
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Study on Color Detection of Korla Fragrant Pears by Near-Infrared Spectroscopy Combined with PLSR by Yifan Xia, Yang Liu, Hong Zhang, Jikai Che, Qing Liang

“…The optimal detection model for the color index L* was SGCD-UVE-PLSR (correlation coefficient (R) = 0.80, Root Mean Square Error (RMSE) = 1.19); for the color index a*, it was VN-SPA-PLSR (R = 0.84 and RMSE = 1.28), and for the color index b*, it was MSC-UVE-PLSR (R = 0.84 and RMSE = 1.25). …”
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Deep reinforcement learning based online lifting path planning for tower cranes in unknown dynamic environments by Kai Wang, Jing Li, Zhiyuan Yin, Jiankang Zhang, Xin Ma

“…Moreover, a novel reward function is introduced to optimize the smoothness of the lifting path, which improves the success rate and optimizes the energy and time cost. …”
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