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Sofía Ramos-Pulido, Neil Hernández-Gress and Gabriela Torres-Delgado
Current research on the career satisfaction of graduates limits educational institutions in devising methods to attain high career satisfaction. Thus, this study aims to use data science models to understand and predict career satisfaction based on infor...
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Minh Tran, Duc Pham-Hi and Marc Bui
In this paper, we propose a novel approach to optimize parameters for strategies in automated trading systems. Based on the framework of Reinforcement learning, our work includes the development of a learning environment, state representation, reward fun...
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Yan Wang, Lei Zhao, Longhao Qiu, Jinjin Wang and Chenmu Li
The underwater maneuvering platform generates self-noise when sailing, which shows spatial directionality to the arrays fixed on the platform. In this paper, it is called spatially colored noise (SCN). The direction of arrival (DOA) estimation results ar...
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Simone Castelli and Andrea Belleri
In recent years, structural health monitoring, starting from accelerometric data, is a method which has become widely adopted. Among the available techniques, machine learning is one of the most innovative and promising, supported by the continuously inc...
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Mandi Liu, Lei Zhang and Qi Yue
Since machine learning is applied in medicine, more and more medical data for prediction has been produced by monitoring patients, such as symptoms information of diabetes. This paper establishes a frame called the Diabetes Medication Bayes Matrix (DTBM)...
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