Catalda Corvasce¹, Juan Pedro Martínez-Ramón^2,*, Francisco Manuel Morales-Rodríguez³, Lidia Pellicer-García⁴, Inmaculada Méndez², Cecilia Ruiz-Esteban²

International Journal of Mental Health Promotion, Vol.26, No.9, pp. 709-718, 2024, DOI:10.32604/ijmhp.2024.053599 - 20 September 2024

Abstract Background: Emotional attention refers to the capacity to recognize and properly respond to one’s and others’ emotional states. On another note, family is a primary source of socialization that influences the development of various social skills. In another line, adolescence is a complex stage that has been associated with emotional difficulties that could be related to competences such as prosociability and inclusion. It is inferred that through the family context and the attention that is processed, a series of competencies are transmitted to the youngsters, but this relationship is still unclear. For this reason, the… More >

Amita U. Dessai^*, Hassanali G. Virani

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1193-1211, 2024, DOI:10.32604/csse.2024.052710 - 13 September 2024

Abstract Emotion recognition is a growing field that has numerous applications in smart healthcare systems and Human-Computer Interaction (HCI). However, physical methods of emotion recognition such as facial expressions, voice, and text data, do not always indicate true emotions, as users can falsify them. Among the physiological methods of emotion detection, Electrocardiogram (ECG) is a reliable and efficient way of detecting emotions. ECG-enabled smart bands have proven effective in collecting emotional data in uncontrolled environments. Researchers use deep machine learning techniques for emotion recognition using ECG signals, but there is a need to develop efficient models… More >

Wen Jiang^1,2, Mingshu Zhang^1,2,*, Xu'an Wang^1,3, Wei Bin^1,2, Xiong Zhang^1,2, Kelan Ren^1,2, Facheng Yan^1,2

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2161-2179, 2024, DOI:10.32604/cmc.2024.053762 - 15 August 2024

Abstract With the rapid spread of Internet information and the spread of fake news, the detection of fake news becomes more and more important. Traditional detection methods often rely on a single emotional or semantic feature to identify fake news, but these methods have limitations when dealing with news in specific domains. In order to solve the problem of weak feature correlation between data from different domains, a model for detecting fake news by integrating domain-specific emotional and semantic features is proposed. This method makes full use of the attention mechanism, grasps the correlation between different… More >

Yi Tang¹, Yajun Zhao², Zihan Jin³, Shengnan Wu^1,*, Zhijun Zhang⁴, Ju Zhou¹, Ling Zhou⁵

International Journal of Mental Health Promotion, Vol.26, No.7, pp. 559-568, 2024, DOI:10.32604/ijmhp.2024.050822 - 30 July 2024

Abstract This study aimed to investigate the relationship between mental health literacy (MHL) and workplace well-being (WWB) of Chinese grassroots civil servants, with regulatory emotional self-efficacy (RESE) and resilience as mediating variables. A questionnaire survey was conducted among Chinese grassroots civil servants, with a valid sample size of 2673 after excluding missing values and conducting relevant data processing. The PROCESS was used to examine the relationship between MHL, RESE, resilience, and WWB. The study found that MHL among grassroots civil servants was positively and significantly correlated with WWB (r = 0.73, p < 0.01). RESE partially mediated… More >

Tao Bao^*, Xiyuan Ma, Zhuohuan Li, Duotong Yang, Pengyu Wang, Changcheng Zhou

Energy Engineering, Vol.121, No.6, pp. 1713-1737, 2024, DOI:10.32604/ee.2023.046150 - 21 May 2024

Abstract The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases. In order to improve and ensure the stable operation of the novel power system, this study proposes an artificial emotional lazy Q-learning method, which combines artificial emotion, lazy learning, and reinforcement learning for static security and stability analysis of power systems. Moreover, this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able More >

J. Sheril Angel¹, A. Diana Andrushia^1,*, T. Mary Neebha¹, Oussama Accouche², Louai Saker², N. Anand³

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2427-2448, 2024, DOI:10.32604/cmc.2024.047326 - 15 May 2024

Abstract Facial emotion recognition (FER) has become a focal point of research due to its widespread applications, ranging from human-computer interaction to affective computing. While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets, recent strides in artificial intelligence and deep learning (DL) have ushered in more sophisticated approaches. The research aims to develop a FER system using a Faster Region Convolutional Neural Network (FRCNN) and design a specialized FRCNN architecture tailored for facial emotion recognition, leveraging its ability to capture spatial hierarchies within localized regions of facial… More >

Zohaib Ahmad Khan¹, Yuanqing Xia^1,*, Ahmed Khan², Muhammad Sadiq², Mahmood Alam³, Fuad A. Awwad⁴, Emad A. A. Ismail⁴

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2771-2793, 2024, DOI:10.32604/cmc.2024.046897 - 15 May 2024

Abstract Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significant source of user-generated content. The development of sentiment lexicons that can support languages other than English is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existing sentiment analysis systems focus on English, leaving a significant research gap in other languages due to limited resources and tools. This research aims to address this gap by building a sentiment lexicon for local languages, which is then used with a machine learning algorithm for efficient sentiment analysis.… More >

Yulei Chen¹, Zhaojun Chen^1,2, Shichao Wang¹, Yang Hang¹, Jianpeng Guo^1,*

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 303-315, 2024, DOI:10.32604/ijmhp.2024.046863 - 04 May 2024

Abstract Social-Emotional Competency (SEC), regarded as a critical psychological resource for individuals to adapt to social environments, is an effective protective factor for students’ mental health, impacting their future success and well-being. Analyzing the impact of SEC on university students’ mental health can offer valuable insights for nurturing talents with healthy psychological and physical development. Based on data from two large-scale surveys of Chinese university students, this study designed two comprehensive Multiple Mediation Models involving SEC, stress, coping strategies, and stress reaction to explore the pathway of emotion nurturing mentality. Study 1 utilized a parallel mediation model… More >

Lin Wang¹, Juan Zhao², Hu Song³, Xiaolong Xu^4,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1105-1135, 2024, DOI:10.32604/cmc.2024.048688 - 25 April 2024

Abstract In smart classrooms, conducting multi-face expression recognition based on existing hardware devices to assess students’ group emotions can provide educators with more comprehensive and intuitive classroom effect analysis, thereby continuously promoting the improvement of teaching quality. However, most existing multi-face expression recognition methods adopt a multi-stage approach, with an overall complex process, poor real-time performance, and insufficient generalization ability. In addition, the existing facial expression datasets are mostly single face images, which are of low quality and lack specificity, also restricting the development of this research. This paper aims to propose an end-to-end high-performance multi-face… More >

Yan Jin, Wei Chen^*

International Journal of Mental Health Promotion, Vol.26, No.3, pp. 189-198, 2024, DOI:10.32604/ijmhp.2023.045331 - 08 April 2024

Abstract An authoritative parenting style has been shown to promote children’s emotion regulation in European-American family studies. However, little is known about how sleep problems and the child’s sibling status in Chinese families affect this relationship. Based on family system theory, this study attempts to better understand the relationship between authoritative parenting style and emotion regulation. Mothers of preschool children in Chinese kindergartens completed questionnaires about their children’s sleep habits, their authoritative parenting styles, and children’s emotion regulation. A total of 531 children participated in this study. Results showed that authoritative parenting was positively associated with… More >