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Sta?a Pu?karic, Mateo Sokac, ?ivana Nincevic, Danijela ?antic, Sanda Skejic, Tomislav D?oic, Heliodor Prelesnik and Knut Yngve Børsheim
In this communication, we present an innovative approach leveraging advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques, specifically the Non-Negative Matrix Factorization (NMF) method, to analyze downward and upward light spectra ...
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Abdelghani Azri, Adil Haddi and Hakim Allali
Collaborative filtering (CF), a fundamental technique in personalized Recommender Systems, operates by leveraging user?item preference interactions. Matrix factorization remains one of the most prevalent CF-based methods. However, recent advancements in ...
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Yusuf Brima, Ulf Krumnack, Simone Pika and Gunther Heidemann
Self-supervised learning (SSL) has emerged as a promising paradigm for learning flexible speech representations from unlabeled data. By designing pretext tasks that exploit statistical regularities, SSL models can capture useful representations that are ...
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Mahsa Kashani, Stefan Jespersen and Zhenyu Yang
The application of deoiling hydrocyclone systems as the downstream of three-phase gravity separator (TPGS) systems is one of the most commonly deployed produced water treatment processes in offshore oil and gas production. Due to the compact system?s com...
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Chin-Yi Chen and Jih-Jeng Huang
Traditional movie recommendation systems are increasingly falling short in the contemporary landscape of abundant information and evolving user behaviors. This study introduced the temporal knowledge graph recommender system (TKGRS), a ground-breaking al...
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Yan Zhou, Kaixuan Zhou and Shuaixian Chen
The rapid development of big data technology and mobile intelligent devices has led to the development of location-based social networks (LBSNs). To understand users? behavioral patterns and improve the accuracy of location-based services, point-of-inter...
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Yanzhong Yin, Qunyong Wu and Mengmeng Li
Understanding intercity mobility patterns is important for future urban planning, in which the intensity of intercity mobility indicates the degree of urban integration development. This study investigates the intercity mobility patterns of the Greater B...
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Gaoyuan Cai, Juhu Li, Xuanxin Liu, Zhibo Chen and Haiyan Zhang
Recently, the deep neural network (DNN) has become one of the most advanced and powerful methods used in classification tasks. However, the cost of DNN models is sometimes considerable due to the huge sets of parameters. Therefore, it is necessary to com...
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Yunfei Zhang, Hongzhen Xu and Xiaojun Yu
An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborativ...
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Yuwen Fu, E. Xia, Duan Huang and Yumei Jing
Machine learning has been applied in continuous-variable quantum key distribution (CVQKD) systems to address the growing threat of quantum hacking attacks. However, the use of machine learning algorithms for detecting these attacks has uncovered a vulner...
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