Color-Sensitive Sensor Array Combined with Machine Learning for Non-Destructive Detection of AFB₁ in Corn Silage by Daqian Wan, Haiqing Tian, Lina Guo, Kai Zhao, Yang Yu, Xinglu Zheng, Haijun Li, Jianying Sun

“…The combined 1st D-PCA-KNN model showed optimal prediction performance, with determination coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mi>p</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> = 0.87), root mean square error (<i>RMSEP</i> = 0.057), and relative prediction deviation (<i>RPD</i> = 2.773). …”
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The value of habitat analysis based on 18F-PSMA-1007 PET/CT images for prostate cancer risk grading by Yang Wang, Hongyue Zhao, Zhehao Lyu, Linhan Zhang, Wei Han, Zeyu Wang, Jiafu Wang, Xinyue Zhang, Shibo Guo, Peng Fu, Changjiu Zhao

“…Abstract Purpose To evaluate the performance of habitat analysis by positron emission tomography (PET)/computed tomography (CT) with 18F-prostate-specific membrane antigen (PSMA)-1007 (18F-PSMA-1007 PET/CT) for prediction of risk grading based on the Gleason Score (GS) for primary prostate cancer (PCa). …”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The experimental results indicate that the prediction results of YOLOv8 are better than those of the other YOLO versions, with a precision rate of 90.32% and a recall rate of 84.91%, which proves that the model can effectively assist physicians in lung cancer diagnosis and improve the accuracy of disease localization and identification.…”
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Virtual Communicative Review of Children’s Art Schools of Irkutsk Region by Dvorovenko Olga

“…The accounts with high engagement rates became involved in social media recommendation algorithms.…”
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An Introduction to the Laplace-Sumudu-Elzaki Transformation and Its Applications in Mathematical Physics by Qike Li, Wei Wang

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A Hybrid Particle Swarm Optimizer for Curriculum Sequencing Problem by Xianjie Peng, Xiaonan Sun, Zhen He

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Modern aspects of diagnostics and treatment of <i>H. pylori</i> infection from standpoint of stomach cancer prophylaxis by A. A. Sheptulin, T. L. Lapina

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Dynamics of striatal action selection and reinforcement learning by Jack W Lindsey, Jeffrey Markowitz, Winthrop F Gillis, Sandeep R Datta, Ashok Litwin-Kumar

“…However, this pathological behavior is reversed if functionally opponent dSPNs and iSPNs, which promote and suppress the current behavior, are simultaneously activated by efferent input following action selection. This prediction is supported by striatal recordings and contrasts with prior models of SPN representations. …”
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Intelligent fault diagnosis and operation condition monitoring of transformer based on multi-source data fusion and mining by Jingping Cui, Wei Kuang, Kai Geng, Pihua Jiao

“…Furthermore, Apriori correlation analysis is performed on the transformer load rate and upper oil layer, winding temperature, and fusion indices of gas components by support and confidence levels to achieve a predictive assessment of the transformer state. Finally, the validity of the algorithm is verified by applying actual data from a power system monitoring platform. …”
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A Cell Component-Related Prognostic Signature for Head and Neck Squamous Cell Carcinoma Based on the Tumor Microenvironment by Siyu Li, Yajun Gu, Junguo Wang, Dengbin Ma, Xiaoyun Qian, Xia Gao

“…The tumor microenvironment (TME) is composed of numerous noncancerous cells that contribute to tumorigenesis and prediction of therapeutic effects. In this study, we aimed to develop a cell component-related prognostic model based on TME. …”
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Molecular function validation and prognostic value analysis of the cuproptosis-related gene ferredoxin 1 in papillary thyroid carcinoma by Shiyue He, Wenzhong Peng, Xinyue Hu, Yong Chen

“…Based on six selected cuproptosis-related genes a predictive prognosis model was established and CRRS displayed a good prediction accuracy. …”
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VAMP-Based Kalman Filtering Under Non-Gaussian Process Noise by Tiancheng Gao, Mohamed Akrout, Faouzi Bellili, Amine Mezghani

“…For the sake of theoretical performance prediction, we conduct a state evolution (SE) analysis of the proposed algorithm and show its consistency with the asymptotic empirical mean-squared error (MSE). …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…Central to these systems are control algorithms, which enable the automation of operations, optimization of process parameters, and reduction of operational costs. …”
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Automated Fillet Weld Inspection Based on Deep Learning from 2D Images by Ignacio Diaz-Cano, Arturo Morgado-Estevez, José María Rodríguez Corral, Pablo Medina-Coello, Blas Salvador-Dominguez, Miguel Alvarez-Alcon

“…In a subsequent experiment, the distinction between a well-manufactured weld bead and a defective one was predicted. In a final experiment, it was possible to predict whether a weld seam was well-manufactured or not, distinguishing between three possible welding defects. …”
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Optimal schedule for extended basic period approach of economic lot scheduling problem by Waldemar Kaczmarczyk

“…Experiments with several problem instances described in the literature confirmed that using the new model within a heuristic algorithm ensures a significant cost reduction for the entire elsp. …”
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A reduced-complexity compressed sensing channel estimation for underwater acoustic channel by Xuan YU, Xuan GENG

“…Aiming at the sparse characteristics of underwater acoustic channels for shallow seas, a reduced-complexity look-ahead backtracking orthogonal matching pursuit (RC-LABOMP) channel estimation algorithm was proposed.Firstly, two types of support sets of orthogonal matching pursuit and subspace pursuit channel estimation algorithms were calculated, and then prior information based on the intersection and union of the two support sets were preprocessed.At last, the preprocessed prior information was used to complete look-ahead backtracking orthogonal matching pursuit channel estimation.The preprocessed prior information leads to the decrease of the iteration number of original LABOMP, and reduction of the atom index range, thus the proposed algorithm can reduce the computational complexity of original LABOMP significantly.In addition, combining the proposed algorithm with the underwater acoustic Turbo equalization system is more suitable for underwater acoustic communication systems.Simulation results show that the proposed algorithm demonstrates high estimation accuracy and low bit error rate performance under both conditions of random channels and underwater acoustic channels.It also reduces the computational complexity of the LABOMP algorithm.Therefore, it is an effective method for shallow seas underwater acoustic channels estimation algorithm.…”
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Measuring the Effectiveness of Carbon-Aware AI Training Strategies in Cloud Instances: A Confirmation Study by Roberto Vergallo, Luca Mainetti

“…Such strategies—natively Cloud-based—use the time resource to postpone or pause the training algorithm when the carbon intensity reaches a threshold. …”
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A reduced-complexity compressed sensing channel estimation for underwater acoustic channel by Xuan YU, Xuan GENG

“…Aiming at the sparse characteristics of underwater acoustic channels for shallow seas, a reduced-complexity look-ahead backtracking orthogonal matching pursuit (RC-LABOMP) channel estimation algorithm was proposed.Firstly, two types of support sets of orthogonal matching pursuit and subspace pursuit channel estimation algorithms were calculated, and then prior information based on the intersection and union of the two support sets were preprocessed.At last, the preprocessed prior information was used to complete look-ahead backtracking orthogonal matching pursuit channel estimation.The preprocessed prior information leads to the decrease of the iteration number of original LABOMP, and reduction of the atom index range, thus the proposed algorithm can reduce the computational complexity of original LABOMP significantly.In addition, combining the proposed algorithm with the underwater acoustic Turbo equalization system is more suitable for underwater acoustic communication systems.Simulation results show that the proposed algorithm demonstrates high estimation accuracy and low bit error rate performance under both conditions of random channels and underwater acoustic channels.It also reduces the computational complexity of the LABOMP algorithm.Therefore, it is an effective method for shallow seas underwater acoustic channels estimation algorithm.…”
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Method of automatic coregistration of digital remote sensing images from different sources by A.N. Borisov, V.V. Myasnikov, V.V. Sergeev

“…To achieve a universal and robust solution in the latter stages, the best-known algorithms were compared: SIFT, SAR-SIFT, RIFT, and the trainable RoMa. …”
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Monocular vision guided deep reinforcement learning UAV systems with representation learning perception by Zhihan Xue, Tad Gonsalves

“…In recent years, numerous studies have applied deep reinforcement learning (DRL) algorithms to vision-guided unmanned aerial systems. …”
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