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http://dx.doi.org/10.1016/j.ultrasmedbio.2015.01.006 | DOI Listing |
PeerJ Comput Sci
November 2024
School of Education, Dankook University, Yongin, Gyeonggi, Republic of South Korea.
To address the issues of data sparsity, scalability, and cold start in the traditional teaching resource recommendation process, this paper presents an enhanced collaborative filtering (CF) recommendation algorithm incorporating a time decay (TD) function. By aligning with the human memory forgetting curve, the TD function is employed as a weighting factor, enabling the calculation of similarity and user preferences constrained by the TD, thus amplifying the weight of user interest over a short period and achieving the integration of short-term and long-term interests. The results indicate that the RMSE of the proposed combined recommendation algorithm (TD-CF) is only 8.
View Article and Find Full Text PDFPhys Chem Chem Phys
December 2024
School of Chemistry and Molecular Bioscience, University of Wollongong, Wollongong, NSW, Australia.
In combustion, acetylene is a key species in molecular-weight growth reactions that form polycyclic aromatic hydrocarbons (PAHs) and ultimately soot particles. Radical addition to acetylene generates a vinyl radical intermediate, which has both and isomers. This isomerism can lead to profound changes in product distributions that are as yet insufficiently investigated.
View Article and Find Full Text PDFBMC Pediatr
December 2024
Division of Pediatric Neurosurgery, Department of Neurosurgery, Faculty of Medicine, Gazi University, Ankara, Turkey.
Background: Arachnoid cysts are extra parenchymal, intra-arachnoid fluid collections of unknown origin, similar in content to cerebrospinal fluid. Suprasellar arachnoid cysts are a rarer localization resulting from abnormalities of the Liliequist membrane or cystic dilatation of the interpeduncular cisterna. We aimed to contribute to the literature by presenting a series of suprasellar arachnoid cyst cases with endoscopic intervention and long-term results.
View Article and Find Full Text PDFInt J Soc Psychiatry
November 2024
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK.
Knowledge tracing is a technology that models students' changing knowledge state over learning time based on their historical answer records, thus predicting their learning ability. It is the core module that supports the intelligent education system. To address the problems of sparse input data, lack of interpretability and weak capacity to capture the relationship between exercises in the existing models, this paper build a deep knowledge tracing model DKVMN&MRI based on the Dynamic Key-Value Memory Network (DKVMN) that incorporates multiple relationship information including exercise-knowledge point relations, exercise-exercise relations, and learning-forgetting relations.
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