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

“…New hydrological insights for the region: This study reveals that the SVR-GWO model has the best performance in predicting flood-prone areas worldwide based on AUC, RMSE and MSE. …”
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Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…With the acceleration of industrialization and the increase in the complexity of equipment, it is particularly important to accurately predict and effectively maintain equipment failures. …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…By implementing the XGBoost algorithm, we established predictive models for defect rate quantification (regression) and defect grade classification. …”
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CMSS1: A RNA binding protein with pivotal roles in non-small cell lung cancer progression and prognosis by Zhe Fan, Wanyu Liu, Zhiwei Gao, Youfa Liu, Hongyang Hai, Zhenyang Lv

“…This study may provide potential guidance for precision therapy and accurate prognosis prediction for patients with NSCLC.…”
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Simulation and Spatio-Temporal Analysis of Soil Erosion in the Source Region of the Yellow River Using Machine Learning Method by Jinxi Su, Rong Tang, Huilong Lin

“…Given these challenges, the objectives of this study were to develop a suitable assessment and prediction model for soil erosion tailored to the SRYR’s needs. …”
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Flood-tech frontiers: smart but just? A systematic review of AI-driven urban flood adaptation and  associated governance challenges by Johannes Bhanye

“…In recent years, Artificial Intelligence (AI) has gained attention as a promising solution in flood risk management, offering capabilities in real-time prediction, risk assessment, decision support, and community engagement. …”
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Federated learning for digital twin applications: a privacy-preserving and low-latency approach by Jie Li, Dong Wang

“…The digital twin (DT) concept has recently gained widespread application for mapping the state of physical entities, enabling real-time analysis, prediction, and optimization, thereby enhancing the management and control of physical systems. …”
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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

“…Computer-supported prediction restricts CSF testing to only 26% of cases, without compromising diagnostic accuracy.…”
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Evaluating Radio Occultation (RO) Constellation Designs Using Observing System Simulation Experiments (OSSEs) for Ionospheric Specification by Nicholas Dietrich, Tomoko Matsuo, Chi‐Yen Lin, Brandon diLorenzo, Charles Chien‐Hung Lin, Tzu‐Wei Fang

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Optimization of ATIG Weld Based on a Swarm Intelligence Approach: Application to the Design of Welding in Selected Manufacturing Processes by Kamel Touileb, Sahbi Boubaker

“…Based on the numerical observations, linear and nonlinear models for describing the effect of the thermophysical parameters on the weld characteristics were tuned using a particle swarm optimization algorithm. While the linear model provided good prediction accuracy, the nonlinear exponential model outperformed the linear one for the depth yielding a mean absolute percentage error of 17%, a coefficient of determination of 0.8266, and a root mean square error of 0.9665 mm. …”
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Drone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans (Phaseolus vulgaris L.) by Leonardo Volpato, Evan M. Wright, Francisco E. Gomez

“…The CNN-LSTM model showed high accuracy in RM prediction across various conditions, outperforming traditional image preprocessing approaches. …”
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Deteksi Cepat Kadar Alkohol Pada Minuman Kopi dengan Metode Dielektrik dan Jaringan Syaraf Tiruan by Sucipto Sucipto, Yuyun Rohmawati, Dyah Ayu Widyaningrum, Danang Triagus Setiyawan

“…The back propagation algorithm was used to connect the input of bioelectric properties and output of prediction of alcohol content and pH in liqueur coffee. …”
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FCB-YOLOv8s-Seg: A Malignant Weed Instance Segmentation Model for Targeted Spraying in Soybean Fields by Zishang Yang, Lele Wang, Chenxu Li, He Li

“…The results of ablation experiments revealed that the FCB-YOLOv8s-Seg model achieved a mean average precision of 95.18% for bounding box prediction and 96.63% for segmentation, marking an increase of 5.08% and 7.43% over the original YOLOv8s-Seg model. …”
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Grapes leaf disease dataset for precision agricultureMendeley Data by Madhuri Dharrao, Nilima Zade, R. Kamatchi, Rakesh Sonawane, Rabinder Henry, Deepak Dharrao

“…This High-quality annotated image dataset can help to design standard advanced AI models for automated disease detection, classification, and prediction. The dataset was validated through a transfer learning approach using the ResNet-18 algorithm and demonstrated the remarkable classification accuracy of 96 %. …”
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Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus by D. Yu. Sorokin, E. S. Trufanova, O. Yu. Rebrova, O. B. Bezlepkina, D. N. Laptev

“…We constructed recurrent neural network (RNN) to predict glucose concentration for 30-120 minutes, an algorithm for optimizing IP settings using prediction results. …”
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Analysis of Temperature Changes, Vegetation, Evapotranspiration, and Drought Based on Modeling of Landsat 5 and 8 Satellite Imagery and Meteorological Indicators by Mitra Sadat Fathifard, Abbas Rahdan, Mahsa Tohidfar

“…Evapotranspiration was then calculated using MODIS data and the Torrent-White method, incorporating the vegetation growth coefficient, and compared with evapotranspiration values derived from the SEBAL algorithm. Additionally, drought prediction was conducted using the Standardized Precipitation Index (SPI) (1-month, 3-month, 6-month, and 12-month) for the period from 2015 to 2044. …”
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Heterogeneity analysis provides evidence for a genetically homogeneous subtype of bipolar-disorder. by Caroline C McGrouther, Aaditya V Rangan, Arianna Di Florio, Jeremy A Elman, Nicholas J Schork, John Kelsoe, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium

“…We first apply this covariate-corrected biclustering algorithm to a cohort of 2524 BD cases and 4106 controls from the Bipolar Disease Research Network (BDRN) within the Psychiatric Genomics Consortium (PGC). …”
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Cost-Efficient Fall Risk Assessment With Attention Augmented Vision Machine Learning on Sit-to-Stand Test Videos by Chunhua Pan, Boting Qu, Rui Miao, Xin Wang

“…Median-average filtering is used to reduce noise caused by video shaking and pose estimation inaccuracies, while a new Dynamic Time Warping (DTW)-based matching algorithm is designed to handle interference from irrelevant individuals appearing in the video. …”
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In Silico Analysis of Coding/Noncoding SNPs of Human RETN Gene and Characterization of Their Impact on Resistin Stability and Structure by Lamiae Elkhattabi, Imane Morjane, Hicham Charoute, Soumaya Amghar, Hind Bouafi, Zouhair Elkarhat, Rachid Saile, Hassan Rouba, Abdelhamid Barakat

“…Stability analysis predicted 9 nsSNPs (I32S, C51Y, G58E, G58R, C78S, G79C, W98C, C103G, and C104Y) which can decrease protein stability with at least three out of the four algorithms used in this study. …”
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Data-Driven Insights into the Association Between Oxidative Stress and Calcium-Regulating Proteins in Cardiovascular Disease by Namuna Panday, Dibakar Sigdel, Irsyad Adam, Joseph Ramirez, Aarushi Verma, Anirudh N. Eranki, Wei Wang, Ding Wang, Peipei Ping

“…By leveraging a link prediction algorithm, our research illuminates the interactions between Ca²⁺-regulating proteins, OS, and CVDs. …”
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