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  • Open Access

    ARTICLE

    A PERT-BiLSTM-Att Model for Online Public Opinion Text Sentiment Analysis

    Mingyong Li, Zheng Jiang*, Zongwei Zhao, Longfei Ma

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2387-2406, 2023, DOI:10.32604/iasc.2023.037900

    Abstract As an essential category of public event management and control, sentiment analysis of online public opinion text plays a vital role in public opinion early warning, network rumor management, and netizens’ personality portraits under massive public opinion data. The traditional sentiment analysis model is not sensitive to the location information of words, it is difficult to solve the problem of polysemy, and the learning representation ability of long and short sentences is very different, which leads to the low accuracy of sentiment classification. This paper proposes a sentiment analysis model PERT-BiLSTM-Att for public opinion text based on the pre-training model… More >

  • Open Access

    REVIEW

    Towards Innovative Research Approaches to Investigating the Role of Emotional Variables in Promoting Language Teachers’ and Learners’ Mental Health

    Ali Derakhshan1, Yongliang Wang2,*, Yongxiang Wang2,*, José Luis Ortega-Martín3

    International Journal of Mental Health Promotion, Vol.25, No.7, pp. 823-832, 2023, DOI:10.32604/ijmhp.2023.029877

    Abstract The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process. Simply said, emotional factors play a key role in improving the quality of language teaching and learning. Furthermore, these emotional factors also promote the well-being of language teachers and learners and place them in a suitable mental condition. In view of the favorable impact of emotional factors on the mental health of language teachers and learners, many educational scholars around the world have studied these factors, their background, and their pedagogical consequences. Nonetheless, the majority of previous studies… More >

  • Open Access

    ARTICLE

    Acknowledge of Emotions for Improving Student-Robot Interaction

    Hasan Han1, Oguzcan Karadeniz1, Tugba Dalyan2,*, Elena Battini Sonmez2, Baykal Sarioglu1

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 1209-1224, 2023, DOI:10.32604/iasc.2023.030674

    Abstract Robot companions will soon be part of our everyday life and students in the engineering faculty must be trained to design, build, and interact with them. The two affordable robots presented in this paper have been designed and constructed by two undergraduate students; one artificial agent is based on the Nvidia Jetson Nano development board and the other one on a remote computer system. Moreover, the robots have been refined with an empathetic system, to make them more user-friendly. Since automatic facial expression recognition skills is a necessary pre-processing step for acknowledging emotions, this paper tested different variations of Convolutional… More >

  • Open Access

    ARTICLE

    An Intervention Study of Language Cognition and Emotional Speech Community Method for Children’s Speech Disorders

    Yali Qiang*

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 627-637, 2023, DOI:10.32604/ijmhp.2023.025746

    Abstract Speech disorders are a common type of childhood disease. Through experimental intervention, this study aims to improve the vocabulary comprehension levels and language ability of children with speech disorders through the language cognition and emotional speech community method. We also conduct a statistical analysis of the interventional effect. Among children with speech disorders in Dongguan City, 224 were selected and grouped according to their receptive language ability and IQ. The 112 children in the experimental group (EG) received speech therapy with language cognitive and emotional speech community, while the 112 children in the control group (CG) only received conventional treatment.… More >

  • Open Access

    ARTICLE

    Construction of Psychological Adjustment Function Model of Music Education Based on Emotional Tendency Analysis

    Bin Zhang*

    International Journal of Mental Health Promotion, Vol.25, No.5, pp. 655-671, 2023, DOI:10.32604/ijmhp.2023.025913

    Abstract In the face of fierce competition in the social environment, mental health problems gradually get the attention of the public, in order to achieve accurate mental health data analysis, the construction of music education is based on emotional tendency analysis of psychological adjustment function model. Design emotional tendency analysis of music education psychological adjustment function architecture, music teaching goal as psychological adjustment function architecture building orientation, music teaching content as a foundation for psychological adjustment function architecture and music teaching process as a psychological adjustment function architecture building, music teaching evaluation as the key of building key regulating function architecture,… More >

  • Open Access

    ARTICLE

    TC-Net: A Modest & Lightweight Emotion Recognition System Using Temporal Convolution Network

    Muhammad Ishaq1, Mustaqeem Khan1,2, Soonil Kwon1,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3355-3369, 2023, DOI:10.32604/csse.2023.037373

    Abstract Speech signals play an essential role in communication and provide an efficient way to exchange information between humans and machines. Speech Emotion Recognition (SER) is one of the critical sources for human evaluation, which is applicable in many real-world applications such as healthcare, call centers, robotics, safety, and virtual reality. This work developed a novel TCN-based emotion recognition system using speech signals through a spatial-temporal convolution network to recognize the speaker’s emotional state. The authors designed a Temporal Convolutional Network (TCN) core block to recognize long-term dependencies in speech signals and then feed these temporal cues to a dense network… More >

  • Open Access

    ARTICLE

    Facial Emotion Recognition Using Swarm Optimized Multi-Dimensional DeepNets with Losses Calculated by Cross Entropy Function

    A. N. Arun1,*, P. Maheswaravenkatesh2, T. Jayasankar2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3285-3301, 2023, DOI:10.32604/csse.2023.035356

    Abstract The human face forms a canvas wherein various non-verbal expressions are communicated. These expressional cues and verbal communication represent the accurate perception of the actual intent. In many cases, a person may present an outward expression that might differ from the genuine emotion or the feeling that the person experiences. Even when people try to hide these emotions, the real emotions that are internally felt might reflect as facial expressions in the form of micro expressions. These micro expressions cannot be masked and reflect the actual emotional state of a person under study. Such micro expressions are on display for… More >

  • Open Access

    ARTICLE

    Parameter Tuned Machine Learning Based Emotion Recognition on Arabic Twitter Data

    Ibrahim M. Alwayle1, Badriyya B. Al-onazi2, Jaber S. Alzahrani3, Khaled M. Alalayah1, Khadija M. Alaidarous1, Ibrahim Abdulrab Ahmed4, Mahmoud Othman5, Abdelwahed Motwakel6,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3423-3438, 2023, DOI:10.32604/csse.2023.033834

    Abstract Arabic is one of the most spoken languages across the globe. However, there are fewer studies concerning Sentiment Analysis (SA) in Arabic. In recent years, the detected sentiments and emotions expressed in tweets have received significant interest. The substantial role played by the Arab region in international politics and the global economy has urged the need to examine the sentiments and emotions in the Arabic language. Two common models are available: Machine Learning and lexicon-based approaches to address emotion classification problems. With this motivation, the current research article develops a Teaching and Learning Optimization with Machine Learning Based Emotion Recognition… More >

  • Open Access

    ARTICLE

    Image Emotion Classification Network Based on Multilayer Attentional Interaction, Adaptive Feature Aggregation

    Xiaorui Zhang1,2,3,*, Chunlin Yuan1, Wei Sun3,4, Sunil Kumar Jha5

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4273-4291, 2023, DOI:10.32604/cmc.2023.036975

    Abstract The image emotion classification task aims to use the model to automatically predict the emotional response of people when they see the image. Studies have shown that certain local regions are more likely to inspire an emotional response than the whole image. However, existing methods perform poorly in predicting the details of emotional regions and are prone to overfitting during training due to the small size of the dataset. Therefore, this study proposes an image emotion classification network based on multilayer attentional interaction and adaptive feature aggregation. To perform more accurate emotional region prediction, this study designs a multilayer attentional… More >

  • Open Access

    ARTICLE

    Short-Term Mindfulness Intervention on Adolescents’ Negative Emotion under Global Pandemic

    Yue Yuan1,*, Aibao Zhou1,*, Tinghao Tang1, Manying Kang2, Haiyan Zhao1, Zhi Wang3

    International Journal of Mental Health Promotion, Vol.25, No.4, pp. 563-577, 2023, DOI:10.32604/ijmhp.2023.022161

    Abstract Objective: In this research, we tried to explore how short-term mindfulness (STM) intervention affects adolescents’ anxiety, depression, and negative and positive emotion during the COVID-19 pandemic. Design: 10 classes were divided into experiment groups (5 classes; n = 238) and control (5 classes; n = 244) randomly. Hospital Anxiety and Depression Scale (HADS) and Positive and Negative Affect Schedule (PANAS) were used to measure participants’ dependent variables. In the experiment group, we conducted STM practice interventions every morning in their first class from March to November 2020. No interventions were conducted in the control group. Methods: Paired-sample t-tests were used to identify if a… More >

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