Integrating the landscape scale supports SAR-based detection and assessment of the phenological development at the field level by Johannes Löw, Steven Hill, Insa Otte, Christoph Friedrich, Michael Thiel, Tobias Ullmann, Christopher Conrad

“…Unlike previous approaches that focus on local algorithm optimisation or SAR feature selection, this work integrates two scales: (1) landscape patterns derived from annual distributions of time series metrics (TSMs) and (2) field-level phenology, both linked to growing degree days (GDD). …”
Get full text

Pathogenetic and substitution correction of anemia in patients with malignant neoplasms by N. A. Romanenko, A. E. Alborov, S. S. Bessmeltsev, E. R. Shilova, S. V. Voloshin, A. V. Chechetkin

“…The doctor can prescribe effective pathogenetic therapy after evaluating the mechanisms of anemia development in this category of patients. …”
Get full text

Pure data correction enhancing remote sensing image classification with a lightweight ensemble model by Huaxiang Song, Hanglu Xie, Yingying Duan, Xinyi Xie, Fang Gan, Wei Wang, Jinling Liu

“…Furthermore, we propose a straightforward algorithm to generate an ensemble network composed of two components, serving as the proposed lightweight classifier. …”
Get full text

Enhancing MANET Security Through Federated Learning and Multiobjective Optimization: A Trust-Aware Routing Framework by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar, Firoz Bin Yusuf Patel Dawoodi

“…This study addresses these challenges by proposing FLSTMT-LAR (Federated Learning Long Short-Term Memory Trust-aware Location-aided Routing), a novel framework that integrates multiobjective optimization with LSTM-based trust prediction for robust routing decisions, implements a decentralized federated learning mechanism for collaborative trust model updates while preserving node privacy, incorporates dynamic trust assessment using LSTM networks for accurate temporal behavior pattern analysis, and provides an adaptive routing decision mechanism that effectively balances multiple performance objectives including trustworthiness, energy efficiency, and network latency. We evaluate this framework against existing protocols across various scenarios, including different network densities, mobility patterns, and malicious node percentages. …”
Get full text

Comparison of the 2021 ESC guideline with the HFA-PEFF and H2FPEF scores in diagnosing heart failure with preserved ejection fraction by Minjae Yoon, Jaewon Oh, Chan Joo Lee, Seok-Min Kang

“…Abstract The HFA-PEFF and H2FPEF scores were recently proposed to help diagnose heart failure (HF) with preserved ejection fraction (HFpEF). We aimed to evaluate HFpEF prevalence according to the 2021 European Society of Cardiology (ESC) HF guideline and the HFA-PEFF and H2FPEF scores in patients with unexplained dyspnea and to compare the concordance between these three algorithms in diagnosing HFpEF. …”
Get full text

Using Attention for Improving Defect Detection in Existing RC Bridges by Sergio Ruggieri, Angelo Cardellicchio, Andrea Nettis, Vito Reno, Giuseppina Uva

“…Visual explanations achieved via the Eigen-CAM algorithm were also exploited to evaluate the reliability of the predictions. …”
Get full text

Fire and Smoke Detection Based on Improved YOLOV11 by Zhipeng Xue, Lingyun Kong, Haiyang Wu, Jiale Chen

“…In addition, the loss function CIOU in YOLOV11 is replaced with IOU to consider the irregular shape of fire and smoke and the problem of multi-scale targets. To evaluate the performance of the algorithm, comprehensive experiments were conducted on two distinct datasets: a public fire and smoke dataset provided by Baidu Paddle featuring close-range views and a public wildfire smoke dataset from the YOLO official website with distant outdoor perspectives. …”
Get full text

Solar Probability Density Estimation Using Adaptive Parametric/Nonparametric Hybrid Model by Maisam Wahbah, Bashar Zahawi, Tarek H. M. El-Fouly

“…The hybrid model is evaluated using multi-year data at six different sites in the United States. …”
Get full text

Do more with less: Exploring semi-supervised learning for geological image classification by Hisham I. Mamode, Gary J. Hampson, Cédric M. John

“…But an alternative exists: there often is a large corpus of unlabeled data which may enhance the learning process. To evaluate this potential for subsurface data, we compare a high-performance semi-supervised learning (SSL) algorithm (SimCLRv2) with supervised transfer learning on a Convolutional Neural Network (CNN) in geological image classification.We tested the two approaches on a classification task of sediment disturbance from cores of International Ocean Drilling Program (IODP) Expeditions 383 and 385. …”
Get full text

Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement by D. Neudecker, T. E. Cutler, M. Devlin, P. Brain, N. Gibson, M. J. Grosskopf, M. W. Herman, J. Hutchinson, T. Kawano, A. Khatiwada, N. Kleedtke, E. Leal-Cidoncha, R. C. Little, A. E. Lovell, A. Stamatopoulos, E. C. Thompson, S. A. Vander Wiel, E. Williamson

“…The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to ^{239}Pu fission cross sections in the desired energy range. …”
Get full text

Identification of prognostic biomarkers associated with stromal cell infiltration in muscle‐invasive bladder cancer by bioinformatics analyses by Pan Li, Jinlong Cao, Jianpeng Li, Zhiqiang Yao, Dali Han, Lijun Ying, Zhiping Wang, Junqiang Tian

“…Bioinformatics analysis of stromal infiltration‐related genes in the tumor microenvironment (TME) of MIBC patients was performed in this study to determine the major stromal cells types and biomarkers for their progression and poor prognosis. The ESTIMATE algorithm was applied to evaluate the stromal score and immune score of samples from MIBC patients in The Cancer Genome Atlas (TCGA) and found that stromal score was closely related to the clinical characteristics of the patients. …”
Get full text

Unveiling global flood hotspots: Optimized machine learning techniques for enhanced flood susceptibility modeling by Mahdi Panahi, Khabat Khosravi, Fatemeh Rezaie, Zahra Kalantari, Jeong-A. Lee

“…All maps produced were evaluated based on root mean square error (RMSE), mean squared error (MSE), standard deviation, and area under the receiver operating characteristic curve (AUC). …”
Get full text

Estimation of Anthropogenic Carbon Dioxide Emissions in China: Remote Sensing with Generalized Regression Neural Network and Partition Modeling Strategy by Chen Chen, Kaitong Qin, Songjie Wu, Bellie Sivakumar, Chengxian Zhuang, Jiaye Li

“…We then applied the Generalized Regression Neural Network model, combined with a partition modeling strategy using the K-means clustering algorithm, to estimate CO₂ emissions based on XCO₂ anomalies, net primary productivity, and population data. …”
Get full text

Graph visualization efficiency of popular web-based libraries by Xin Zhao, Xuan Wang, Xianzhe Zou, Huiming Liang, Genghuai Bai, Ning Zhang, Xin Huang, Fangfang Zhou, Ying Zhao

“…These libraries allow users to call application programming interfaces (APIs) without identifying the details of the encapsulated techniques such as graph layout algorithms and graph rendering methods. Efficiency requirements, such as visualizing a graph with 3k nodes and 4k edges within 1 min at a frame rate of 30 fps, are crucial for selecting a proper library because libraries generally present different characteristics owing to the diversity of encapsulated techniques. …”
Get full text

Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…Recognizing the strengths and limitations of the LSTM model, we propose a hybrid machine-learning algorithm that integrates LSTM with a physics-based model. …”
Get full text

Building a machine learning-based risk prediction model for second-trimester miscarriage by Sangsang Qi, Shi Zheng, Mengdan Lu, Aner Chen, Yanbo Chen, Xianhu Fu

“…Seven machine-learning models were built and subjected to a comprehensive analysis to validate and evaluate their predictive capabilities. Through this rigorous assessment, the optimal model was selected. …”
Get full text

Selection of memory clinic patients for CSF biomarker assessment can be restricted to a quarter of cases by using computerized decision support, without compromising diagnostic acc... by Hanneke F M Rhodius-Meester, Ingrid S van Maurik, Juha Koikkalainen, Antti Tolonen, Kristian S Frederiksen, Steen G Hasselbalch, Hilkka Soininen, Sanna-Kaisa Herukka, Anne M Remes, Charlotte E Teunissen, Frederik Barkhof, Yolande A L Pijnenburg, Philip Scheltens, Jyrki Lötjönen, Wiesje M van der Flier

“…Tools that guide in selecting patients in which CSF biomarkers have clinical utility are needed. We evaluated computerized decision support to select patients for CSF biomarker determination.…”
Get full text

Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, one more challenge is the significant variance in speech signals caused by factors such as different speakers, content, acoustic settings, language differences, changes in voice modulation based on age and gender, and variations in speech patterns. …”
Get full text

Advancing Sika deer detection and distance estimation through comprehensive camera calibration and distortion analysis by Sandhya Sharma, Stefan Baar, Bishnu P. Gautam, Shinya Watanabe, Satoshi Kondo, Kazuhiko Sato

“…Using the cv2.TM_CCOEFF_NORMED template matching algorithm with templates scaled from 0.01 to 2.0 and a confidence threshold of 0.6, the resolution threshold was defined as the distance at which the observed circle size deviated from the expected size. …”
Get full text

Development of <i>OptiCon</i>: A Mathematical Model with a Graphical User Interface for Designing Sustainable Portland Cement Concrete Mixes with Budget Constraint by Angie Pineda, Rita Peñabaena-Niebles, Gilberto Martínez-Arguelles, Rodrigo Polo-Mendoza

“…The proposed model, denominated <i>OptiCon</i>, employs the Life-Cycle Assessment and Life-Cycle Costs Analysis methodologies to evaluate the incorporation of three different SCMs (i.e., fly ash, silica fume, and steel slag) and RCA into PCC mixes. …”
Get full text