Evaluating rice crop phenology and crop yield in hilly region using satellite imagery and Google Earth Engine by SHWETA POKHARIYAL, N.R. PATEL, AJEET SINGH NAIN, AKARSH S.G., R.S. RANA, R.K. SINGH, RAJEEV RANJAN

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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…More accurate tracking and lower identity switches make this algorithm more suitable to be used in the field of autonomous driving. …”
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Implementing E-MOTIVE for detection and treatment of postpartum haemorrhage in South Africa by M Singata-Madliki, S Fawcus, N Moran, E Arends, E Muller, S Mandondo, G J Hofmeyr

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QSAR, Molecular Docking, and Pharmacokinetic Studies of 1,8-Naphthyridine Derivatives as Potential Anticancer Agents Targeting DNA Topoisomerase II by Garba Suleiman, Auwal Salisu Isa, Adamu Uzairu, Nabil El Brahmi, Saïd El Kazzouli

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Executive summary: indonesian guidelines on polycystic ovary syndrome management by Mila Maidarti, Achmad Kemal Harzif, Amalia Shadrina, Nafi'atul Ummah, Wiryawan Permadi

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A machine learning based radiomics approach for predicting No. 14v station lymph node metastasis in gastric cancer by Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Tingting Ma, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Mengran Zhao, Xiangli Li, Xiangchao Song, Xiangchao Song, Xiangchao Song, Xiangchao Song, Lingwei Wang, Lingwei Wang, Lingwei Wang, Lingwei Wang, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye, Zhaoxiang Ye

“…The diagnostic ability of the signature and model were evaluated.ResultsLR algorithm was chosen for signature construction. The radiomics signature exhibited good discrimination accuracy of 14vM with AUCs of 0.83 in the training and 0.77 in the testing set. …”
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Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
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Analysis of reservoir rock permeability changes due to solid precipitation during waterflooding using artificial neural network by Azizollah Khormali, Soroush Ahmadi, Aleksandr Nikolaevich Aleksandrov

“…The ANN model using the Levenberg-Marquardt (LM) algorithm showed superior performance with the lowest mean squared error (MSE) for training, testing, and all data sets. …”
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Handling method for GPS outages based on PSO-LSTM and fading adaptive Kalman filtering by Xiaoming Li, Xianchen Wang, Can Pei

“…Abstract To mitigate the degradation in GPS/INS integrated navigation performance during GPS signal outages, a PSO-optimized LSTM method is proposed to predict the pseudo position. The PSO algorithm is utilized to optimize two hyperparameters, neuron count and learning rate, which are essential to improve the training efficiency and prediction accuracy in the LSTM model. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The model is based on TBESO (Multi-strategy Boosted Snake Optimizer) and utilizes monthly Dairy Herd Improvement (DHI) data to forecast the status of subclinical mastitis in cows.Materials and methodsThe Monthly Dairy Herd Improvement (DHI) data spanning from January 2022 to July 2022 (full dataset) was partitioned into both the training and testing datasets. TBESO addresses the challenge associated with erratic initial weights and thresholds in the BP neural network, impacting training outcomes. …”
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Measuring professional preparedness of would-be teachers for pedagogical activity based on criteria-level estimation by M. A. Golovchin

“…In particular, it concerns the inner desire to see oneself in pedagogical activity as an established professional, which is not always formed in the process of training at vocational schools and universities (especially if admission to the major was associated with “negative selection”). …”
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A new approach for diabetes risk detection using quadratic interpolation flower pollination neural network by Yulianto Triwahyuadi POLLY, Adriana FANGGIDAE, Juan Rizky Mannuel LEDOH, Clarissa Elfira AMOS PAH, Bertha S. DJAHI, Kisan Emiliano Rape TUPEN

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Development and clinical application of an automated machine learning-based delirium risk prediction model for emergency polytrauma patients by Zhenyi Liu, Yihao Huang, Long Li, Yisha Xu, Peng Wu, Zhigang Zhang, Tingyong Han, Liangjie Zhang, Ming Zhang

“…The SHapley Additive exPlanations (SHAP) framework quantified predictor contributions, and a MATLAB-based clinical decision support system (CDSS) was implemented for real-time risk stratification.ResultsThe improved algorithm significantly outperformed other algorithms on 12 standard test functions. …”
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Low-Fidelity, In Situ, Accessible Pediatric Mass Casualty Incident Simulation to Evaluate and Improve Pediatric Readiness by Sydney E. Jeffs, Cathlyn K. Medina, Parker Frankiewicz, Steven W. Thornton, Elizabeth Horne, Smith Ngeve, Tara Thomason, Delaney Anani-Wolf, Catherine B. Beckhorn, Delaney James, Rachel Hobbs, Remi Hueckel, Corrie E. Chumpitazi, Erin R. Hanlin, Rachel O'Brian, Elisabeth T. Tracy, Emily Greenwald

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Intelligent Dual Basal–Bolus Calculator for Multiple Daily Insulin Injections via Offline Reinforcement Learning by Junyoung Yoo, Vega Pradana Rachim, Suyeon Jung, Sung-Min Park

“…The offline phase utilized historical insulin treatment data to train the model, reducing the risks associated with real-time learning. …”
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USE OF NONSTEROIDAL ANTI-INFLAMMATORY DRUGS FOR THE TREATMENT OF AXIAL SPONDYLOARTHRITIS, INCLUDING ANKYLOSING SPONDYLITIS, MONITORING THEIR EFFICACY AND SAFETY (DRAFT GUIDELINES O... by I. Z. Gaidukova, A. P. Rebrov, E. N. Otteva, V. V. Badokin, A. G. Bochkova, O. V. Bugrova, A. A. Godzenko, A. A. Dubikov, T. V. Dubinina, O. N. Ivanova, T. V. Korotaeva, S. A. Lapshina, O. B. Nesmeyanova, I. P. Nikishina, T. A. Raskina, O. A. Rumyantseva, A. V. Smirnov, A. V. Sitalo, Sh. F. Erdes

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Leveraging Genomic Annotations and Pleiotropic Enrichment for Improved Replication Rates in Schizophrenia GWAS. by Yunpeng Wang, Wesley K Thompson, Andrew J Schork, Dominic Holland, Chi-Hua Chen, Francesco Bettella, Rahul S Desikan, Wen Li, Aree Witoelar, Verena Zuber, Anna Devor, Bipolar Disorder and Schizophrenia Working Group of the Psychiatric Genomics Consortium, Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, Markus M Nöthen, Marcella Rietschel, Qiang Chen, Thomas Werge, Sven Cichon, Daniel R Weinberger, Srdjan Djurovic, Michael O'Donovan, Peter M Visscher, Ole A Andreassen, Anders M Dale

“…We apply this approach to the recent genome-wide association study (GWAS) of SCZ (n = 82,315), obtaining a good fit between the model-based and observed effect sizes and replication probabilities. …”
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Research on the Construction and Application of Earthquake Emergency Information Knowledge Graph Based on Large Language Models by Wentao Zhou, Meng Huang, Shuai Liu, Qiao You, Fanxin Meng

“…The path confidence constraint algorithm (PCCA) is used to achieve deep semantic associations of earthquake disaster elements. …”
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A Formal Approach to Optimally Configure a Fully Connected Multilayer Hybrid Neural Network by Goutam Chakraborty, Vadim Azhmyakov, Luz Adriana Guzman Trujillo

“…We have developed an equivalent, optimal control-based formulation of the given problem of training a hybrid feedforward multilayer neural network, to train the target mapping function constrained by the training samples. …”
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The development of scientific and methodological provisions in the application of artificial neural networks by Babkin Alexander, Ponomareva Svetlana, Serebryansky Daniil, Mustafaev Timur, Nosirov Ilkhom

“…The relevance of the research topic in the field of artificial intelligence is associated with the growing interest in introducing independent intelligence through self-learning artificial neural networks, the need to expand the field of space research, reducing cosmonaut training and space objects research, as well as significant funds allocated to the subject under study. …”
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