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Sangsung Park and Sunghae Jun
Cognitive artificial intelligence (CAI) is an intelligent machine that thinks and behaves similar to humans. CAI also has an ability to mimic human emotions. With the development of AI in various fields, the interest and demand for CAI are continuously i...
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Maxime Gobert, Jan Gmys, Jean-François Toubeau, Nouredine Melab, Daniel Tuyttens and François Vallée
Bayesian Optimization (BO) with Gaussian process regression is a popular framework for the optimization of time-consuming cost functions. However, the joint exploitation of BO and parallel processing capabilities remains challenging, despite intense rese...
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Wenjun Bai, Changqin Quan and Zhiwei Luo
Featured Application: The proposed Uncertainty Flow framework may benefit the facial analysis with its promised elevation in discriminability in multi-label affective classification tasks. Moreover, this framework also allows the efficient model training...
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Yaseen A. Hamaamin, Amir Pouyan Nejadhashemi, Zhen Zhang, Subhasis Giri and Sean A. Woznicki
Accurate and efficient estimation of streamflow in a watershed?s tributaries is prerequisite parameter for viable water resources management. This study couples process-driven and data-driven methods of streamflow forecasting as a more efficient and cost...
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Yaseen A. Hamaamin, Amir Pouyan Nejadhashemi, Zhen Zhang, Subhasis Giri, Sean A. Woznicki
Pág. 1 - 15
Accurate and efficient estimation of streamflow in a watershed?s tributaries is prerequisite parameter for viable water resources management. This study couples process-driven and data-driven methods of streamflow forecasting as a more efficient and cost...
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Arturo J. Fernández
Confidence regions for the Weibull parameters with minimum areas among all those based on the Conditionality Principle are constructed using an equivalent diffuse Bayesian approach. The process is valid for scenarios involving standard failure and progre...
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Jordi Mas-Soler, Antonio Souto-Iglesias and Alexandre N. Simos
An innovative Bayesian motion-based wave inference method is derived and assessed in this work. The evaluation of the accuracy of the proposed prior distribution has been carried out using the results obtained during a dedicated experimental campaign wit...
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Jared A. Cook, Ralph C. Smith, Jason M. Hite, Razvan Stefanescu and John Mattingly
Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous de...
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J Gerard Wolff
This article is an overview of the SP theory of intelligence, which aims to simplify and integrate concepts across artificial intelligence, mainstream computing and human perception and cognition, with information compression as a unifying theme. It is c...
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Yiyi Wang, Kara M. Kockelman, Xiaokun (Cara) Wang
Pág. 75 - 85
This paper develops two new models and evaluates the impact of using different weight matrices on parameter estimates and inference in three distinct spatial specifications for discrete response. These specifications rely on a conventional, sparse, inver...
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Ji-Yoon Kim and Chae-Kwan Lim
The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers. However, due to data sparsity, the recommenda...
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Pavlos Toukiloglou and Stelios Xinogalos
This paper reviews the research on adaptive serious games for programming regarding the implementation of their support systems. Serious games are designed to educate players in an entertaining and engaging manner. A key element in terms of meeting their...
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Camil Bancioiu and Remus Brad
This article proposes the usage of the d-separation criterion in Markov Boundary Discovery algorithms, instead of or alongside the statistical tests of conditional independence these algorithms usually rely on. This is a methodological improvement applic...
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Ang Su, Liang Zhang, Xuefeng Zhang, Shaoqing Zhang, Zhao Liu, Caili Liu and Anmin Zhang
Due to the model and sampling errors of the finite ensemble, the background ensemble spread becomes small and the error covariance is underestimated during filtering for data assimilation. Because of the constraint of computational resources, it is diffi...
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Ignacio Rodríguez-Rodríguez, José-Víctor Rodríguez, José-María Molina-García-Pardo, Miguel-Ángel Zamora-Izquierdo and María-Teresa Martínez-Inglés Ignacio Martínez-Inglés
The metabolic disease Type 1 Diabetes Mellitus (DM1) is caused by a reduction in the production of pancreatic insulin, which causes chronic hyperglycemia. Patients with DM1 are required to perform multiple blood glucose measurements on a daily basis to m...
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Sema Atasever, Zafer Aydin, Hasan Erbay and Mostafa Sabzekar
Predicting the secondary structure from protein sequence plays a crucial role in estimating the 3D structure, which has applications in drug design and in understanding the function of proteins. As new genes and proteins are discovered, the large size of...
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