'Fruit' machine with novice and expert modes

• 1. 利用受专家意见监督的决策模式学习的用于机器维护的决策辅助系统和方法 [P] . 中国专利： CN108027611B . 2021.05.04
• 2. 利用受专家意见监督的决策模式学习的用于机器维护的决策辅助系统和方法 [P] . 中国专利： CN108027611A . 2018-05-11
• 3. Interactive wagering using multiple types of interfaces for expert and novice users [P] . NZ516103A . 2004-05-28

  机译： 使用面向专家和新手用户的多种类型的界面进行交互式投注

• 4. PRIORITIZING TASKS OF DOMAIN EXPERTS FOR MACHINE LEARNING MODEL TRAINING [P] . US2021065054A1 . 2021-03-04

  机译： 用于机器学习模型培训的领域专家的优先级任务

• 5. DYNAMIC HARDWARE SELECTION FOR EXPERTS IN MIXTURE-OF-EXPERTS MODEL [P] . 美国专利： US2019188577A1 . 2019-06-20

  机译： 专家混合模型中的动态硬件选择

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• 2. Quantifying muskmelon fruit attributes with A-TEP-based model and machine vision measurement [J] . CHANG Li-ying, HE San-peng, LIU Qian, 农业科学学报：英文版 . 2018,第006期
• 3. Using Visual Notations with Modeling Experts or Novices: What do the Experts Think? [C] . Dirk van der Linden Advanced information systems engineering workshops . 2017
• 4. Modeling the reasoning processes in experts and novices' argument diagramming task: Sequential analysis of diagramming behavior and think-aloud data [D] . Kim, Hae Young 2015
• 5. Joint action coordination in expert-novice pairs: Can experts predict novices’ suboptimal timing? [O] . Thomas Wolf, Natalie Sebanz, Günther Knoblich -1
• 6. We develop a model of scientific creativity and test it in the field of rare diseases. Our model is based on the results of an in-depth case study of the Rett syndrome. Archival analysis, bibliometric techniques and expert surveys are combined with network analysis to identify the most creative scientists. First, alternative measures of generative and combinatorial creativity are compared. Then, we generalize our results and present a stochastic model of socio-semantic network evolution. The model predictions are tested with multiple networks of rare disease specialties. We find that new scientific collaborations among experts in a field enhance combinatorial creativity. Instead, high entry rates of novices are negatively related to generative creativity. By extending the set of useful concepts, creative scientists gain in centrality. At the same time, by increasing their centrality in the scientific community, scientists can replicate and generalize their results, thus contributing to a scientific paradigm. [O] . Massimo Riccaboni, Maria Laura Frigotto 100
• 7. Mental Models for Effective Training: Comparing Expert and Novice Maintainers' Mental Models [R] . Hubal, R. C. 2009

• 1. A Comparative Study of the Planning and Preparation Strategies of Novice,Proficient and Expert Teachers in Chinese Middle School [J] . 郭成城 . 海外英语 . 2018,第15期
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• 3. Heteroscedastic Laplace mixture of experts regression models and applications [J] . WU Liu-cang ,ZHANG Shu-yu ,LI Shuang-shuang . 高校应用数学学报B辑 . 2021,第001期
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