Blasting is the live wire of mining and its operations,with air overpressure(AOp)recognised as an end product of blasting.AOp is known to be one of the most important environmental hazards of mining.Further research i...Blasting is the live wire of mining and its operations,with air overpressure(AOp)recognised as an end product of blasting.AOp is known to be one of the most important environmental hazards of mining.Further research in this area of mining is required to help improve on safety of the working environment.Review of previous studies has shown that many empirical and artificial intelligence(AI)methods have been proposed as a forecasting model.As an alternative to the previous methods,this study proposes a new class of advanced artificial neural network known as brain inspired emotional neural network(BIENN)to predict AOp.The proposed BI-ENN approach is compared with two classical AOp predictors(generalised predictor and McKenzie formula)and three established AI methods of backpropagation neural network(BPNN),group method of data handling(GMDH),and support vector machine(SVM).From the analysis of the results,BI-ENN is the best by achieving the least RMSE,MAPE,NRMSE and highest R,VAF and PI values of 1.0941,0.8339%,0.1243%,0.8249,68.0512%and 1.2367 respectively and thus can be used for monitoring and controlling AOp.展开更多
Teacher emotion recognition(TER)has a significant impact on student engagement,classroom atmosphere,and teaching quality,which is a research hotspot in the smart education area.However,existing studies lack high-quali...Teacher emotion recognition(TER)has a significant impact on student engagement,classroom atmosphere,and teaching quality,which is a research hotspot in the smart education area.However,existing studies lack high-quality multimodal datasets and neglect common and discriminative features of multimodal data in emotion expression.To address these challenges,this research constructs a multimodal TER dataset suitable for real classroom teaching scenarios.TER dataset contains a total of 102 lessons and 2,170 video segments from multiple educational stages and subjects,innovatively labelled with emotional tags that characterize teacher‒student interactions,such as satisfaction and questions.To explore the characteristics of multimodal data in emotion expression,this research proposes an emotion dual-space network(EDSN)that establishes an emotion commonality space construction(ECSC)module and an emotion discrimination space construction(EDSC)module.Specifically,the EDSN utilizes central moment differences to measure the similarity to assess the correlation between multiple modalities within the emotion commonality space.On this basis,the gradient reversal layer and orthogonal projection are further utilized to construct the EDSC to extract unique emotional information and remove redundant information from each modality.Experimental results demonstrate that the EDSN achieves an accuracy of 0.770 and a weighted F1 score of 0.769 on the TER dataset,outperforming other comparative models.展开更多
An increasing body of neuroimaging and electrophysiological studies of the brain suggest that the insular cortex（IC） integrates multimodal salient information ranging from sensation to cognitive-affective events to ...An increasing body of neuroimaging and electrophysiological studies of the brain suggest that the insular cortex（IC） integrates multimodal salient information ranging from sensation to cognitive-affective events to create conscious interoception. Especially with regard to pain experience, the IC has been supposed to participate in both sensory-discriminative and affective-motivational aspects of pain. In this review, we discuss the latest data proposing that subregions of the IC are involved in isolated pain networks： the posterior sensory circuit and the anterior emotional network. Due to abundant connections with other brain areas, the IC is likely to serve as an interface where cross-modal shaping of pain occurs. In chronic pain,however, this mode of emotional awareness and the modulation of pain are disrupted. We highlight some of the molecular mechanisms underlying the changes of the pain modulation system that contribute to the transition from acute to chronic pain in the IC.展开更多
At present, the emotion classification method of Weibo public opinions based on graph neural network cannot solve the polysemy problem well, and the scale of global graph with fixed weight is too large. This paper pro...At present, the emotion classification method of Weibo public opinions based on graph neural network cannot solve the polysemy problem well, and the scale of global graph with fixed weight is too large. This paper proposes a feature fusion network model Bert-TextLevelGCN based on BERT pre-training and improved TextGCN. On the one hand, Bert is introduced to obtain the initial vector input of graph neural network containing rich semantic features. On the other hand, the global graph connection window of traditional TextGCN is reduced to the text level, and the message propagation mechanism of global sharing is applied. Finally, the output vector of BERT and TextLevelGCN is fused by interpolation update method, and a more robust mapping of positive and negative sentiment classification of public opinion text of “Tangshan Barbecue Restaurant beating people” is obtained. In the context of the national anti-gang campaign, it is of great significance to accurately and efficiently analyze the emotional characteristics of public opinion in sudden social violence events with bad social impact, which is of great significance to improve the government’s public opinion warning and response ability to public opinion in sudden social security events. .展开更多
基金This work was supported by the Ghana National Petroleum Corporation(GNPC)through the GNPC Professorial Chair in Mining Engineering at the University of Mines and Technology(UMaT),GhanaThe authors thank the Ghana National Petroleum Corporation(GNPC)for providing funding to support this work through the GNPC Professorial Chair in Mining Engineering at the University of Mines and Technology(UMaT),Ghana.
文摘Blasting is the live wire of mining and its operations,with air overpressure(AOp)recognised as an end product of blasting.AOp is known to be one of the most important environmental hazards of mining.Further research in this area of mining is required to help improve on safety of the working environment.Review of previous studies has shown that many empirical and artificial intelligence(AI)methods have been proposed as a forecasting model.As an alternative to the previous methods,this study proposes a new class of advanced artificial neural network known as brain inspired emotional neural network(BIENN)to predict AOp.The proposed BI-ENN approach is compared with two classical AOp predictors(generalised predictor and McKenzie formula)and three established AI methods of backpropagation neural network(BPNN),group method of data handling(GMDH),and support vector machine(SVM).From the analysis of the results,BI-ENN is the best by achieving the least RMSE,MAPE,NRMSE and highest R,VAF and PI values of 1.0941,0.8339%,0.1243%,0.8249,68.0512%and 1.2367 respectively and thus can be used for monitoring and controlling AOp.
基金supported by the National Natural Science Foundation of China(Grant Nos.62377007 and 62407009)the Chongqing University Graduate Education Teaching Reform Research Key Project,China(Grant No.232073)+1 种基金the Scientific and Technological Research Program of Chongqing Municipal Education Commission,China(Grant Nos.KJZD-M202400606 and KJZD-M202300603)the Chongqing Natural Science Foundation Joint Key Project for Innovation and Development,China(Grant No.2024NSCQ-LZX0057).
文摘Teacher emotion recognition(TER)has a significant impact on student engagement,classroom atmosphere,and teaching quality,which is a research hotspot in the smart education area.However,existing studies lack high-quality multimodal datasets and neglect common and discriminative features of multimodal data in emotion expression.To address these challenges,this research constructs a multimodal TER dataset suitable for real classroom teaching scenarios.TER dataset contains a total of 102 lessons and 2,170 video segments from multiple educational stages and subjects,innovatively labelled with emotional tags that characterize teacher‒student interactions,such as satisfaction and questions.To explore the characteristics of multimodal data in emotion expression,this research proposes an emotion dual-space network(EDSN)that establishes an emotion commonality space construction(ECSC)module and an emotion discrimination space construction(EDSC)module.Specifically,the EDSN utilizes central moment differences to measure the similarity to assess the correlation between multiple modalities within the emotion commonality space.On this basis,the gradient reversal layer and orthogonal projection are further utilized to construct the EDSC to extract unique emotional information and remove redundant information from each modality.Experimental results demonstrate that the EDSN achieves an accuracy of 0.770 and a weighted F1 score of 0.769 on the TER dataset,outperforming other comparative models.
基金supported by the National Natural Science Foundation of China(31371120)the Foundation for Returned Overseas Students of Ministry of Education,China(HG3503)
文摘An increasing body of neuroimaging and electrophysiological studies of the brain suggest that the insular cortex（IC） integrates multimodal salient information ranging from sensation to cognitive-affective events to create conscious interoception. Especially with regard to pain experience, the IC has been supposed to participate in both sensory-discriminative and affective-motivational aspects of pain. In this review, we discuss the latest data proposing that subregions of the IC are involved in isolated pain networks： the posterior sensory circuit and the anterior emotional network. Due to abundant connections with other brain areas, the IC is likely to serve as an interface where cross-modal shaping of pain occurs. In chronic pain,however, this mode of emotional awareness and the modulation of pain are disrupted. We highlight some of the molecular mechanisms underlying the changes of the pain modulation system that contribute to the transition from acute to chronic pain in the IC.
文摘At present, the emotion classification method of Weibo public opinions based on graph neural network cannot solve the polysemy problem well, and the scale of global graph with fixed weight is too large. This paper proposes a feature fusion network model Bert-TextLevelGCN based on BERT pre-training and improved TextGCN. On the one hand, Bert is introduced to obtain the initial vector input of graph neural network containing rich semantic features. On the other hand, the global graph connection window of traditional TextGCN is reduced to the text level, and the message propagation mechanism of global sharing is applied. Finally, the output vector of BERT and TextLevelGCN is fused by interpolation update method, and a more robust mapping of positive and negative sentiment classification of public opinion text of “Tangshan Barbecue Restaurant beating people” is obtained. In the context of the national anti-gang campaign, it is of great significance to accurately and efficiently analyze the emotional characteristics of public opinion in sudden social violence events with bad social impact, which is of great significance to improve the government’s public opinion warning and response ability to public opinion in sudden social security events. .
