47 research outputs found
Leveraging Emotional AI for Improved Human Computer Interactions : An Interdisciplinary Perspective
No full textEmotions are psychophysiological processes that are sparked by both conscious and unconscious perceptions of things and events. Mood, motivation, temperament, and personality are frequently linked to emotions. Human-machine interaction will see the creation of systems that can recognize and interpret human emotions in a range of ways as computers and computer-based applications get more advanced and pervasive in people’s daily lives. More sympathetic and customized relationships between humans and machines can result from efficient emotion recognition in human-machine interactions. Emotion recognition systems are able to modify their responses and user experience based on the analysis of interpersonal communication signals. The ability of virtual assistants to respond emotionally more effectively,
the ability to support mental health systems by identifying users’ emotional states, the improvement of customer support interactions with emotionally responsive Chabots, and the enhancement of human robot collaboration are just a few examples of real-world applications. Reviewing the interpersonal
communication elements of the emotional interaction models that are now in use is the aim of this chapter
Emotion Recognition in Human-Machine Interaction and a Review in Interpersonal Communication Perspective
No full textEmotions are fundamental to daily decision-making and overall wellbeing. Emotions are psychophysiological processes that are frequently linked to human-machine interaction, and it is expected we will see the creation of systems that can recognize and interpret human emotions in a range of ways as computers and computer-based applications get more advanced and pervasive in people's daily lives. Emotion recognition systems are able to modify their responses and user experience based on the analysis of interpersonal communication signals. The ability of virtual assistants to respond emotionally more effectively, the ability to support mental health systems by identifying users' emotional states, and the enhancement of human-machine interaction applications. The aim of this chapter is reviewing the interpersonal communication elements of the emotional interaction models that are now
Education and Training Revolution : A Review on AR, VR, and IoT Integration in Educational Perspective
No full textAugmented reality (AR), virtual reality (VR), and the Internet of Things (IoT) have changed the way learning. AR, VR, and IoT are a few of the most important in training and education. AR and VR give students a variety of interactive experiences that can help them understand and retain complex concepts. These technologies allow students to experiment with real life scenarios, visualize ideas, and do virtual research. IoT combines physical and digital platforms to create a smart learning environment that enables real time data collection, analysis, and feedback. Interdependence not only facilitates adaptive assessments and effective classroom management but also facilitates personalized educational programs. Chapter presents case studies and empirical research that demonstrate the efficacy of AR, VR, and IoT across a broad spectrum of educational levels, including primary, secondary, and professional education, as well as training and professional programs. It also addresses affordability, accessibility, and the need for teacher training to incorporate new technologies into the curriculum. The chapter highlights the potential of AR, VR, and IoT in fostering inclusive, innovative, and dynamic learning environments, while also exploring future prospects through current trends and IoT
A nonlinear anisotropic diffusion model with forward-backward diffusivities for image denoising
No full text
AN EMPIRICAL STUDY ON WHETHER FACEBOOK PROMOTION CAN DELIVER VALUE TO INDIAN START-UPS?
No full textStartups face challenges in investing large amounts of money in business promotion due to resource constraints and operational size. Hence, business promotion strategies like advertising, public relations, sales promotions, billboards, and event sponsorship are generally avoided by startup companies. Instead, Startups tend to employ social media strategies to run promotional campaigns on platforms like Facebook, Twitter, Instagram, and YouTube, among others. However, there is a paucity of research to understand whether such promotional campaigns are delivering the desired value and able to achieve the objectives set by the startups. The present study makes an endeavor to explore whether promotions through social media are effective in delivering significant outcome to startups. Therefore, this study aims to empirically investigate whether Facebook Promotion is delivering value to Indian startups. To conduct the research, cross-sectional data has been collected from 100 startup located in different cities in India. The data has been analyzed following the “Partial Least Squared-Structural Equation Modelling (PLS-SEM)” technique. The findings from this study may contribute towards the literature on understanding the importance of social media strategies in marketing campaigns for startups. Furthermore, this study may enhance clarity about the value obtained by startups, particularly during the early stage of their existence. Consequently, the study findings may help startups plan their investments in promoting their products and services on social media, in general, and Facebook, in particular
