Machine Learning-Based Environment-Aware GNSS Integrity Monitoring for Urban Air Mobility by Oguz Kagan Isik, Ivan Petrunin, Antonios Tsourdos

“…This study introduces a novel machine learning-based GNSS integrity monitoring framework that incorporates environment recognition to create environment-specific error models. Using a comprehensive Hardware-in-the-Loop (HIL) simulation setup, extensive data were generated for suburban, urban, and urban canyon environments to train and validate the models. …”
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ICESat-2 Performance for Terrain and Canopy Height Retrieval in Complex Mountainous Environments by Lianjin Fu, Qingtai Shu, Cuifen Xia, Zeyu Li, Xiao Zhang, Yiran Zhang

“…Nighttime strong-beam acquisitions substantially improved accuracies for both products. This research demonstrates ICESat-2’s viability for high-resolution digital terrain modeling and provides quality control thresholds for forest structure estimation in challenging regions, addressing validation gaps in Asian biodiversity hotspots and supporting carbon monitoring for UN Sustainable Development Goals.…”
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Multi-objective optimization of the heating oil circuit inside the calendering roller for the lithium battery pole piece by Shuangqiu Sun, Junqiang Wang, Rongying Zhang, Zhenchao Si, Zhijie Yang

“…In the multi-objective optimization procedure, an integrated optimization framework is established by the prebuilt CAD module and the FEM module in the commercial software. Then, the improved NSGA-II algorithm is selected to execute the optimization loop. …”
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Three-Dimensional Drone Cell Placement: Drone Placement for Optimal Coverage by Aniket Basu, Hooman Oroojeni, Georgios Samakovitis, Mohammad Majid Al-Rifaie

“…Algorithmic diversity has been explored, leading to several modifications and improvements in the implemented models. …”
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Information and methodological aspects of developing platforms of spatial management of natural assets in resource limitations by V.V. Mykytenko, I.V. Dragan

“…The structure, content and functions of information and methodological support of the system of spatial management of natural resource assets of the platform type are improved. It includes a set of target programs MiNerGy v.5.0 and MINprojet v.3, where the algorithm of two blocks to perform economic-statistical and stochastic counter-forecasts, used, along with standard packages «Statistica +» and Windows-applications Excel, Access (included in the author's technologies) tool environment of cognitive-information systems of the third intellectual level, which are developed using neural networks Neiro Pro 0.25 and Brain Maker 3.11.…”
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Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…This study presents a comprehensive numerical investigation of the Laser Powder Bed Fusion (LPBF) process for pure molybdenum, focusing on high-precision modeling and process optimization. The powder spreading behavior is simulated using the Discrete Element Method (DEM), while molten pool dynamics are analyzed through Computational Fluid Dynamics (CFD). …”
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Evaluation of parameters extracted from tissue residue functions in dynamic susceptibility contrast MRI: Healthy volunteers examined during normal breathing and spontaneous hyperve... by Ronnie Wirestam, Arthur Chakwizira, Peter Reinstrup

“…The applied Bézier curve deconvolution algorithm returned tissue residue functions of plausible shapes, i.e., without oscillations and negative values, and some indications that curve shape is relevant for improved assessment of oxygen extraction properties were demonstrated.…”
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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Firstly, a parametric geometric modeling approach is developed to define measurement spaces for individual features, accompanied by an innovative maximal complete subgraph mining algorithm to intelligently identify shared feasible measurement regions among multiple features. …”
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Transcriptome signature for multiple biotic and abiotic stress in barley (Hordeum vulgare L.) identifies using machine learning approach by Bahman Panahi

“…The C4.5 algorithm demonstrated superior accuracy in predicting stress-responsive signatures. …”
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Disruption of tumor-intrinsic PGAM5 increases anti-PD-1 efficacy through the CCL2 signaling pathway by Yan Li, Hong Wang, Xiaoyang Li, Yuan He, Huiquan Liu, Dong Han, Ting Mei, Yixuan Li, Zilong Xu, Xiaoying Wei, Jianguo Wang, Peijie Zhou, Yuwen Wang, Ziye Li, Junhao Ning, Anlin Wang, Jingjing Cheng, Dong Qian

“…Macrophages were depleted to investigate whether the effects of tumor-intrinsic PGAM5 on TAMs could affect immunotherapy efficacy in HCC orthotopic and subcutaneous mouse models.Results PGAM5 expression in tumor was positively correlated with M2-phenotype TAM infiltration in patients with both HCC and mouse HCC tumor models. …”
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Artificial intelligence as a diagnostic aid in cross-sectional radiological imaging of the abdominopelvic cavity: a protocol for a systematic review by Natalie S Blencowe, Neil J Smart, George E Fowler, Rhiannon C Macefield, Conor Hardacre, Mark P Callaway

“…This may improve the performance of diagnostic, prognostic and management decisions. …”
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An Efficient Deep Learning-Based Framework for Predicting Cyber Violence in Social Networks by Younes Fayand Fathabad, Mohammad Ali Balafar, Amin Golzari Oskouei, Kamal Koohi

“…Deep learning-based algorithms have proven effective in identifying violent content, yet existing models often struggle with understanding contextual nuances and implicit forms of cyber violence. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
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High-accuracy combustible gas cloud imaging system using YOLO-plume classification network by Jiani Zhou, Yang Liu, Yong Zhang, Haotian Hu, Zenan Leng, Feng Sun, Chen Chen

“…Experimental results show that the proposed model achieves an F1-score of 88.97% and an IoU of 89.74%, improving upon the baseline by 7.37% and 7.59%, respectively, with a detection accuracy reaching 99.78%.…”
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AC-YOLO: citrus detection in the natural environment of orchards by Xu Xiao, Yaonan Wang, Yiming Jiang, Haotian Wu, Zhe Zhang, Rujing Wang

“…The panorama image is divided into sub images, and an improved YOLOV4 model is used for recognition. By comparing the orange recognition effects of different network models such as Fast R-CNN, Center Net, YOLOV4 series algorithms, and YOLOV5 series algorithms on the panorama image, the improved YOLOV4 network model has an accuracy rate of 96.19%, a recall rate of 95.47%, and an average accuracy of 97.27%, Compared with the original YOLOv4 model, it has increased by 1.07, 2.59, and 2.02 percentage points respectively. …”
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A Critical Review of the Prospect of Integrating Artificial Intelligence in Infectious Disease Diagnosis and Prognosis by Shuaibu Abdullahi Hudu, Ahmed Subeh Alshrari, Esra’a Jebreel Ibrahim Abu-Shoura, Amira Osman, Abdulgafar Olayiwola Jimoh

“…This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. …”
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Integration of the Adaptive Approach in HVAC System Operation: A Case Study by Pablo Aparicio-Ruiz, J. C. Ragel-Bonilla, Elena Barbadilla-Martín, José Guadix

“…The results indicate that it is possible to develop adaptive comfort models that ensure the thermal well-being of occupants. …”
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Thermal Cracking Analysis of Microbial Cemented Sand under Various Strains Based on the DEM by Yang Tang, Guobin Xu, Yue Yan, Dengfeng Fu, Chunlai Qu, Zilong Li, Evance Chaima

“…Three kinds of experiments, X-ray diffraction (XRD), X-ray computed tomography (XCT), and scanning electron microscopy (SEM), were conducted to explore the composition, shape, and bonding characteristics of physical assemblies in this paper. A precision DEM modelling of MCS, mainly composed of irregular particle modelling and a mesoparameter calibration algorithm, has been proposed for the thermal cracking analysis under various strains (i.e., 1.0‰–3.0‰). …”
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Random Forest–Based Coal Mine Roof Displacement Prediction and Application by Hongxia Li, Rong Wu, Jianan Gao

“…Based on Random Forest (RF), XGBoost, and Gradient Boosting Decision Tree (GBDT) algorithms, three kinds of roof displacement prediction models are established respectively. …”
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Red-KPLS Feature Reduction with 1D-ResNet50: Deep Learning Approach for Multiclass Alzheimer’s Staging by Syrine Neffati, Ameni Filali, Kawther Mekki, Kais Bouzrara

“…Compared to conventional models, our approach improves classification robustness and generalization, reinforcing its potential for scalable and interpretable AD diagnostics. …”
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