This research article presents a comprehensive study on the pre-training of two language models, MorRoBERTa and MorrBERT, for the Moroccan Dialect, using the Masked Language Modeling (MLM) pre-training approach. The s...
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In dynamic manufacturing contexts, the Job-Shop Scheduling Problem (JSP) presents considerable hurdles, particularly in light of uncertainties such as machine breakdowns and job reworks. In this article, multiple sche...
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In this paper, we developed a method to calculate the time parameters for interfacing with code message sources (CMS). This method enables the evaluation of how the collection and delivery time of information from CMS...
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The article presents a method for cluster analysis of heterogeneous data using the provisions of fuzzy logic. Heterogeneous are data of various formats and collected from various sources. In addition, such data is usu...
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The article discusses the methodology for modeling a digital twin of an automated production process. The basis of the methodology is the method of intellectual analysis and information processing, which involves iden...
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The article substantiates the need to use neural network algorithms to search for mature crops and optimize harvesting equipment routes based on the data obtained. A technique for detecting fruit maturity based on the...
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Internet banking is nowadays an important platform for taking care of financial matters. Researchers have introduced the acceptance of internet banking, which allows users to fulfil their obligations without visiting ...
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The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications....
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The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.
Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenar...
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Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).
XYZ University has an Alpha Application used during the registration process for student courses each semester. There must be a hazard in the installation of this informationsystem that could impede the process or fu...
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