AI-Enhanced Disaster Management: A Modular OSINT System for Rapid Automated Reporting by Klaus Schwarz, Kendrick Bollens, Daniel Arias Aranda, Michael Hartmann

“…ODET enables the implementation of AI-enhanced algorithms to respond to various complex disaster scenarios. …”
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A comprehensive approach to predict a rocket's impact with stochastic estimators and artificial neural networks by Jose Abreu, Roberto L. Oliveira, Joao V. Fonseca Neto

“…This approach combines tracking algorithms that are based on stochastic estimators with artificial neural network (ANN) models. …”
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An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles by Prot Piyakawanich, Pattarapong Phasukkit

“…By synergistically combining K-Means Clustering with a multiple-input deep learning regression-based model (DL-KMA), we have achieved substantial improvements in altitude estimation accuracy. …”
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A Device for the Rapid Detection of Benzodiazepines and Synthetic Cannabinoids via Fluorescence Spectroscopy and Machine Learning by A. Power, M. Gardner, C. Pudney

“…Results: Development of the first prototype of the device is nearing completion, and lab data has been collected for training the device's drug-detecting predictive model. Current experiments with established supervised-learning algorithms show favourable results in distinguishing Synthetic Cannabinoids. …”
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Service quality evaluation of integrated health and social care for older Chinese adults in residential settings based on factor analysis and machine learning by Zhihan Liu, Caini Ouyang, Nian Gu, Jiaheng Zhang, Xiaojiao He, Qiuping Feng, Chunguyu Chang

“…Comparative indices such as Mean Squared Error, Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and predictive performance metrics were employed to assess the models. Results The service quality evaluation model, enhanced by factor analysis and fuzzy BPNN, demonstrated reduced error rates and improved predictive performance metrics. …”
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Machine learning Techniques for Spondylolisthesis Diagnosis: a review by Rahma Rabee Aziz, Mohammed S. Jarjees, Mohammad R. Aziz, Ali Asim Hameed

“…This review highlights how deep learning and machine learning models can improve spondylolisthesis diagnosis, enabling enhanced diagnosis and treatment methods. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Feature selection method impacts radiomics models’ performance more than ML algorithms. Best feature selection methods: RFE, LASSO, RF, and Boruta. …”
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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…In addition, the improved Channel Attention Concatenation (CAC) strategy adaptively learns channel-wise importance weights during feature concatenation, further optimizing multi-scale semantic feature fusion and enhancing the model’s sensitivity to critical crater features. …”
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AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…For instance, ResNet-18 achieved impressive results, outperforming other models. Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. …”
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REU-Net: A Remote Sensing Image Building Segmentation Network Based on Residual Structure and the Edge Enhancement Attention Module by Tianen Yuan, Bo Hu

“…Furthermore, a hybrid loss function combining edge consistency loss and binary cross-entropy loss is used to train the network, aiming to improve segmentation accuracy. Experimental results show that REU-Net(2EEAM) achieves optimal performance across multiple evaluation metrics (such as P, MPA, MIoU, and FWIoU), particularly excelling in the accurate recognition of building edges, significantly outperforming other network models. …”
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Analysis of Energy Sustainability and Problems of Technological Process of Primary Aluminum Production by Yury Valeryevich Ilyushin, Egor Andreevich Boronko

“…The results of this study can be used to improve the energy efficiency and environmental friendliness of aluminum production.…”
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Artificial intelligence as one of the key drivers of the economy digital transformation by O.I. Pizhuk

“…Artificial intelligence technologies represent a unique opportunity for us to transform business operations by reducing the number of repetitive, routine tasks, significantly increase productivity, create new products, create new models of economic growth, and improve the efficiency of government agencies, especially at the level of development of solutions aimed at ensuring the well-being of citizens. …”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…Abstract This study aims to verify the performance of an electric tractor equipped with a four-wheel independent driving (4WID) electric axle (E-axle) system through simulation analysis using a MATLAB/Simulink model. The simulation model was validated through bench testing to ensure accuracy and reliability. …”
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High-resolution surface soil moisture retrieval: A hybrid machine learning framework integrating change detection and downscaling for precision water management by Zihao Wang, Qi Gao, Michele Crosetto, Maria Jose Escorihuela

“…Among the evaluated algorithms, XGBoost model performed best, achieving an R2 of 0.933 and RMSE of 0.023 cm3/cm3. …”
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Remote monitoring of Tai Chi balance training interventions in older adults using wearable sensors and machine learning by Giulia Corniani, Stefano Sapienza, Gloria Vergara-Diaz, Andrea Valerio, Ashkan Vaziri, Paolo Bonato, Peter M. Wayne

“…Our framework comprises a model for identifying the specific Tai Chi movement being performed and a model to assess performance proficiency, both employing Random Forest algorithms and features from IMU signals. …”
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Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines. by Takuro Matsuta, Ryo Furue

“…In contrast, QA using the D-Wave quantum annealing machine fails to obtain good solutions for some cases owing to hardware limitations; in particular, the highly limited connectivity graph of the machine limits the size of the solvable problems, at least under currently available algorithms. Either expanding the machine's connectivity graph or improving the graph-embedding algorithms would probably be necessary for quantum annealing machines to be usable for oceanic and atmospheric dynamics problems.…”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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Integrating GIS and remote sensing for soil attributes mapping in degraded pastures of the Brazilian Cerrado by Rômullo Oliveira Louzada, Ivan Bergier, Édson Luis Bolfe, Jayme Garcia Arnal Barbedo

“…Results showed that Boruta-enhanced models (T2 + T4) improved performance in 89 % of cases. …”
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Artificial intelligence in breast cancer survival prediction: a comprehensive systematic review and meta-analysis by Zohreh Javanmard, Saba Zarean Shahraki, Kosar Safari, Abbas Omidi, Sadaf Raoufi, Mahsa Rajabi, Mohammad Esmaeil Akbari, Mehrad Aria

“…Such endeavors will not only validate the efficacy of these models across diverse populations but also pave the way for their integration into clinical practice, ultimately contributing to personalized patient care and improved survival outcomes.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier CRD42024513350.…”
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Research of Regenerative Braking Strategy for Electric Vehicles by Van Nghia Le, Hoang Phuc Dam, Trong Hoan Nguyen, S. V. Kharitonchik, V. A. Kusyak

“…The carried out investigations confirm the available significant potential for improving the efficiency of the electric vehicles usage by developing the control strategy and algorithms of the braking energy regeneration.…”
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