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  • 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

    A Deep Learning Model to Analyse Social-Cyber Psychological Problems in Youth

    Ali Alqazzaz1, Mohammad Tabrez Quasim1,*, Mohammed Mujib Alshahrani1, Ibrahim Alrashdi2, Mohammad Ayoub Khan1

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 551-562, 2023, DOI:10.32604/csse.2023.031048

    Abstract Facebook, Twitter, Instagram, and other social media have emerged as excellent platforms for interacting with friends and expressing thoughts, posts, comments, images, and videos that express moods, sentiments, and feelings. With this, it has become possible to examine user thoughts and feelings in social network data to better understand their perspectives and attitudes. However, the analysis of depression based on social media has gained widespread acceptance worldwide, other verticals still have yet to be discovered. The depression analysis uses Twitter data from a publicly available web source in this work. To assess the accuracy of depression detection, long-short-term memory (LSTM)… More >

  • Open Access

    ARTICLE

    Human-Computer Interaction Using Deep Fusion Model-Based Facial Expression Recognition System

    Saiyed Umer1,*, Ranjeet Kumar Rout2, Shailendra Tiwari3, Ahmad Ali AlZubi4, Jazem Mutared Alanazi4, Kulakov Yurii5

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1165-1185, 2023, DOI:10.32604/cmes.2022.023312

    Abstract A deep fusion model is proposed for facial expression-based human-computer Interaction system. Initially, image preprocessing, i.e., the extraction of the facial region from the input image is utilized. Thereafter, the extraction of more discriminative and distinctive deep learning features is achieved using extracted facial regions. To prevent overfitting, in-depth features of facial images are extracted and assigned to the proposed convolutional neural network (CNN) models. Various CNN models are then trained. Finally, the performance of each CNN model is fused to obtain the final decision for the seven basic classes of facial expressions, i.e., fear, disgust, anger, surprise, sadness, happiness,… More >

  • Open Access

    ARTICLE

    Emotions, Perceptions and Health Behaviors of Adult Congenital Heart Disease Patients during COVID-19 in New York City

    Jodi L. Feinberg1, Peter Sheng2, Stephanie Pena2, Adam J. Small1, Susanna Wendelboe1, Katlyn Nemani3, Vikram Agrawal4, Dan G. Halpern1,*

    Congenital Heart Disease, Vol.17, No.5, pp. 519-531, 2022, DOI:10.32604/chd.2022.024174

    Abstract Background: Adults with congenital heart disease (ACHD) have increased prevalence of mood and anxiety disorders. There are limited data regarding the influence of the COVID-19 pandemic on the mental health and health behaviors of these patients. Objective: The purpose is to evaluate the perceptions, emotions, and health behaviors of ACHD patients during the COVID-19 pandemic. Methods: In this cross-sectional study of ACHD patients, we administered surveys evaluating self-reported emotions, perceptions and health behaviors. Logistic regressions were performed to determine the adjusted odds of displaying each perception, emotion and health behavior based on predictor variables. Results: Ninety-seven patients (mean age 38.3… More > Graphic Abstract

    Emotions, Perceptions and Health Behaviors of Adult Congenital Heart Disease Patients during COVID-19 in New York City

  • Open Access

    ARTICLE

    Human Emotions Classification Using EEG via Audiovisual Stimuli and AI

    Abdullah A Asiri1, Akhtar Badshah2, Fazal Muhammad3,*, Hassan A Alshamrani1, Khalil Ullah4, Khalaf A Alshamrani1, Samar Alqhtani5, Muhammad Irfan6, Hanan Talal Halawani7, Khlood M Mehdar8

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5075-5089, 2022, DOI:10.32604/cmc.2022.031156

    Abstract Electroencephalogram (EEG) is a medical imaging technology that can measure the electrical activity of the scalp produced by the brain, measured and recorded chronologically the surface of the scalp from the brain. The recorded signals from the brain are rich with useful information. The inference of this useful information is a challenging task. This paper aims to process the EEG signals for the recognition of human emotions specifically happiness, anger, fear, sadness, and surprise in response to audiovisual stimuli. The EEG signals are recorded by placing neurosky mindwave headset on the subject’s scalp, in response to audiovisual stimuli for the… More >

  • Open Access

    ARTICLE

    NLP-Based Subject with Emotions Joint Analytics for Epidemic Articles

    Woo Hyun Park1, Isma Farah Siddiqui2, Dong Ryeol Shin1, Nawab Muhammad Faseeh Qureshi3,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2985-3001, 2022, DOI:10.32604/cmc.2022.028241

    Abstract For the last couple years, governments and health authorities worldwide have been focused on addressing the Covid-19 pandemic; for example, governments have implemented countermeasures, such as quarantining, pushing vaccine shots to minimize local spread, investigating and analyzing the virus’ characteristics, and conducting epidemiological investigations through patient management and tracers. Therefore, researchers worldwide require funding to achieve these goals. Furthermore, there is a need for documentation to investigate and trace disease characteristics. However, it is time consuming and resource intensive to work with documents comprising many types of unstructured data. Therefore, in this study, natural language processing technology is used to… More >

  • Open Access

    ARTICLE

    Negative Emotions Sensitive Humanoid Robot with Attention-Enhanced Facial Expression Recognition Network

    Rongrong Ni1, Xiaofeng Liu1,*, Yizhou Chen1, Xu Zhou1, Huili Cai1, Loo Chu Kiong2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 149-164, 2022, DOI:10.32604/iasc.2022.026813

    Abstract Lonely older adults and persons restricted in movements are apt to cause negative emotions, which is harmful to their mental health. A humanoid robot with audiovisual interactions is presented, which can correspondingly output positive facial expressions to relieve human's negative facial expressions. The negative emotions are identified through an attention-enhanced facial expression recognition (FER) network. The network is firstly trained on MMEW macro-and micro-expression databases to discover expression-related features. Then, macro-expression recognition tasks are performed by fine-tuning the trained models on several benchmarking FER databases, including CK+ and Oulu-CASIA. A transformer network is introduced to process the sequential features engineered… More >

  • Open Access

    ARTICLE

    Facial Action Coding and Hybrid Deep Learning Architectures for Autism Detection

    A. Saranya1,*, R. Anandan2

    Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1167-1182, 2022, DOI:10.32604/iasc.2022.023445

    Abstract Hereditary Autism Spectrum Disorder (ASD) is a neuron disorder that affects a person's ability for communication, interaction, and also behaviors. Diagnostics of autism are available throughout all stages of life, from infancy through adolescence and adulthood. Facial Emotions detection is considered to be the most parameter for the detection of Autismdisorders among the different categories of people. Propelled with a machine and deep learning algorithms, detection of autism disorder using facial emotions has reached a new dimension and has even been considered as the precautionary warning system for caregivers. Since Facial emotions are limited to only seven expressions, detection of… More >

  • Open Access

    ARTICLE

    Emotion Based Signal Enhancement Through Multisensory Integration Using Machine Learning

    Muhammad Adnan Khan1,2, Sagheer Abbas3, Ali Raza3, Faheem Khan4, T. Whangbo4,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5911-5931, 2022, DOI:10.32604/cmc.2022.023557

    Abstract Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming signals. It is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place, the signal having more strength under the influence of emotions effects the response accordingly. Current research in multisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or depression. Therefore, there is a need to integrate the emotional state of the agent with… More >

  • Open Access

    ARTICLE

    BERT-CNN: A Deep Learning Model for Detecting Emotions from Text

    Ahmed R. Abas1, Ibrahim Elhenawy1, Mahinda Zidan2,*, Mahmoud Othman2

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671

    Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective of this paper is to… More >

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