Attention allocation research frequently focuses on the valence of emotion. However, there is increasing evidence to indicate that arousal may be more relevant at some stages of affective processing. The present study...Attention allocation research frequently focuses on the valence of emotion. However, there is increasing evidence to indicate that arousal may be more relevant at some stages of affective processing. The present study employed a combined priming and cue-target paradigm and examined event-related potentials (ERPs) in order to explore the effects of emotional conflict of arousal on attention allocation. The background context of arousal was manipulated (using photos of facial expressions) while subjects performed a cognitive task in which a central arrow cue indicated the location of a peripheric target square, and a response was made according to the direction of the square. There was no main effect between incongruent emotion and congruent emotion in the response time, which means the resolution of the emotional conflict facilitate the participant behavioral response. There was a main effect of different emotional states on ERP component. In the present study, incongruent arousal also triggered greater positive potential compared with congruent arousal.展开更多
Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation.While traditional methods for task allocation can help reduce costs and improve efficiency,they may encoun...Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation.While traditional methods for task allocation can help reduce costs and improve efficiency,they may encounter challenges when dealing with abnormal data flow nodes,leading to decreased allocation accuracy and efficiency.To address these issues,this study proposes a novel two-part invalid detection task allocation framework.In the first step,an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous data.Compared to the baseline method,the model achieves an approximately 4%increase in the F1 value on the public dataset.In the second step of the framework,task allocation modeling is performed using a twopart graph matching method.This phase introduces a P-queue KM algorithm that implements a more efficient optimization strategy.The allocation efficiency is improved by approximately 23.83%compared to the baseline method.Empirical results confirm the effectiveness of the proposed framework in detecting abnormal data nodes,enhancing allocation precision,and achieving efficient allocation.展开更多
It is essential to ensure that teachers allocate adequate attention to homework evaluation and effectively carry it out in order to successfully implement the"double reduction"policy.From the perspective of ...It is essential to ensure that teachers allocate adequate attention to homework evaluation and effectively carry it out in order to successfully implement the"double reduction"policy.From the perspective of teachers'attention allocation,this study employed the NVivo 12 software to conduct text analysis on 39 cases of homework evaluation reform practices in primary and secondary schools in City N,China,from 2017 to 2021.The findings indicate that homework evaluation reform in these schools is a practical problem-oriented behavioral decision,and implementing the"double reduction"policy enhances teachers'attention allocation on homework evaluation.The attention allocation of teachers encompasses multiple aspects,such as determining the purpose of evaluation,setting evaluation content,and selecting evaluation subjects and methods.Following the implementation of the"double reduction"policy,teachers allocate more attention to reducing the homework burden on students.However,certain issues persist in the practices of homework evaluation reform,including inadequate consideration of constraints,an unbalanced content structure,and a lack of process coordination.Therefore,under the"double reduction"policy,it is imperative to improve school incentive systems,enhance teachers'evaluation capabilities,and alleviate their workload.These measures can guide teachers to allocate more attention to homework evaluation,thereby enhancing the efficiency and sustainability of attention allocation and fully realizing the educational function of homework evaluation.展开更多
Human Attention Allocation Strategy (HAAS) is related closely to operating performance when he/she is interacting a machine through a human-machine interface. Gaze behaviors, which is acquisited by eye tracking techno...Human Attention Allocation Strategy (HAAS) is related closely to operating performance when he/she is interacting a machine through a human-machine interface. Gaze behaviors, which is acquisited by eye tracking technology, can be used to observe attention allocation. But the performance-sensitive attention allocation strategy is still hard to measure using gaze cue. In this paper, we attempt to understand visual attention allocation behavior and reveal the relationship between attention allocation strategy and interactive performance in a quantitative manner. By using a novel Multiple-Level Clustering approach, we give some results on probabilistic analysis about interactive performance of HAAS patterns in a simulation platform of thermal-hydraulic process plant. It can be observed that these patterns are sensitive to interactive performance. We conclude that our Multiple-Level Clustering approach can extract efficiently human attention allocation patterns and evaluate interactive performance using gaze movements.展开更多
文摘Attention allocation research frequently focuses on the valence of emotion. However, there is increasing evidence to indicate that arousal may be more relevant at some stages of affective processing. The present study employed a combined priming and cue-target paradigm and examined event-related potentials (ERPs) in order to explore the effects of emotional conflict of arousal on attention allocation. The background context of arousal was manipulated (using photos of facial expressions) while subjects performed a cognitive task in which a central arrow cue indicated the location of a peripheric target square, and a response was made according to the direction of the square. There was no main effect between incongruent emotion and congruent emotion in the response time, which means the resolution of the emotional conflict facilitate the participant behavioral response. There was a main effect of different emotional states on ERP component. In the present study, incongruent arousal also triggered greater positive potential compared with congruent arousal.
基金National Natural Science Foundation of China(62072392).
文摘Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource allocation.While traditional methods for task allocation can help reduce costs and improve efficiency,they may encounter challenges when dealing with abnormal data flow nodes,leading to decreased allocation accuracy and efficiency.To address these issues,this study proposes a novel two-part invalid detection task allocation framework.In the first step,an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous data.Compared to the baseline method,the model achieves an approximately 4%increase in the F1 value on the public dataset.In the second step of the framework,task allocation modeling is performed using a twopart graph matching method.This phase introduces a P-queue KM algorithm that implements a more efficient optimization strategy.The allocation efficiency is improved by approximately 23.83%compared to the baseline method.Empirical results confirm the effectiveness of the proposed framework in detecting abnormal data nodes,enhancing allocation precision,and achieving efficient allocation.
基金funded by the Education Science Planning of Hubei Province in 2021,"Research on the Regional Education Optimal Path for Promoting High-Quality Professional Development of Teachers"(No.2021JB196)funded by the Basic Scientific Research Business Fund for Central Universities of Central China Normal University,"Research on Educational Evaluation in Primary and Secondary Schools in the Context of the New College Entrance Examination"(No.CCNU20DC009).
文摘It is essential to ensure that teachers allocate adequate attention to homework evaluation and effectively carry it out in order to successfully implement the"double reduction"policy.From the perspective of teachers'attention allocation,this study employed the NVivo 12 software to conduct text analysis on 39 cases of homework evaluation reform practices in primary and secondary schools in City N,China,from 2017 to 2021.The findings indicate that homework evaluation reform in these schools is a practical problem-oriented behavioral decision,and implementing the"double reduction"policy enhances teachers'attention allocation on homework evaluation.The attention allocation of teachers encompasses multiple aspects,such as determining the purpose of evaluation,setting evaluation content,and selecting evaluation subjects and methods.Following the implementation of the"double reduction"policy,teachers allocate more attention to reducing the homework burden on students.However,certain issues persist in the practices of homework evaluation reform,including inadequate consideration of constraints,an unbalanced content structure,and a lack of process coordination.Therefore,under the"double reduction"policy,it is imperative to improve school incentive systems,enhance teachers'evaluation capabilities,and alleviate their workload.These measures can guide teachers to allocate more attention to homework evaluation,thereby enhancing the efficiency and sustainability of attention allocation and fully realizing the educational function of homework evaluation.
基金Project supported by theNationalNature Science Foundation ofChina (No. 61471252) and the Natural Science Foundation of Jiangsu Province (No. BK20130303).
文摘Human Attention Allocation Strategy (HAAS) is related closely to operating performance when he/she is interacting a machine through a human-machine interface. Gaze behaviors, which is acquisited by eye tracking technology, can be used to observe attention allocation. But the performance-sensitive attention allocation strategy is still hard to measure using gaze cue. In this paper, we attempt to understand visual attention allocation behavior and reveal the relationship between attention allocation strategy and interactive performance in a quantitative manner. By using a novel Multiple-Level Clustering approach, we give some results on probabilistic analysis about interactive performance of HAAS patterns in a simulation platform of thermal-hydraulic process plant. It can be observed that these patterns are sensitive to interactive performance. We conclude that our Multiple-Level Clustering approach can extract efficiently human attention allocation patterns and evaluate interactive performance using gaze movements.
