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Open Access
Article
Publication date: 4 October 2022

Dhong Fhel K. Gom-os and Kelvin Y. Yong

The goal of this study is to test the real-world use of an emotion recognition system.

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Abstract

Purpose

The goal of this study is to test the real-world use of an emotion recognition system.

Design/methodology/approach

The researchers chose an existing algorithm that displayed high accuracy and speed. Four emotions: happy, sadness, anger and surprise, are used from six of the universal emotions, associated by their own mood markers. The mood-matrix interface is then coded as a web application. Four guidance counselors and 10 students participated in the testing of the mood-matrix. Guidance counselors answered the technology acceptance model (TAM) to assess its usefulness, and the students answered the general comfort questionnaire (GCQ) to assess their comfort levels.

Findings

Results from TAM found that the mood-matrix has significant use for the guidance counselors and the GCQ finds that the students were comfortable during testing.

Originality/value

No study yet has tested an emotion recognition system applied to counseling or any mental health or psychological transactions.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 13 March 2018

Ulla Gain

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human…

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Abstract

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

Details

Applied Computing and Informatics, vol. 16 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 26 August 2021

Shruti Garg, Rahul Kumar Patro, Soumyajit Behera, Neha Prerna Tigga and Ranjita Pandey

The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.

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Abstract

Purpose

The purpose of this study is to propose an alternative efficient 3D emotion recognition model for variable-length electroencephalogram (EEG) data.

Design/methodology/approach

Classical AMIGOS data set which comprises of multimodal records of varying lengths on mood, personality and other physiological aspects on emotional response is used for empirical assessment of the proposed overlapping sliding window (OSW) modelling framework. Two features are extracted using Fourier and Wavelet transforms: normalised band power (NBP) and normalised wavelet energy (NWE), respectively. The arousal, valence and dominance (AVD) emotions are predicted using one-dimension (1D) and two-dimensional (2D) convolution neural network (CNN) for both single and combined features.

Findings

The two-dimensional convolution neural network (2D CNN) outcomes on EEG signals of AMIGOS data set are observed to yield the highest accuracy, that is 96.63%, 95.87% and 96.30% for AVD, respectively, which is evidenced to be at least 6% higher as compared to the other available competitive approaches.

Originality/value

The present work is focussed on the less explored, complex AMIGOS (2018) data set which is imbalanced and of variable length. EEG emotion recognition-based work is widely available on simpler data sets. The following are the challenges of the AMIGOS data set addressed in the present work: handling of tensor form data; proposing an efficient method for generating sufficient equal-length samples corresponding to imbalanced and variable-length data.; selecting a suitable machine learning/deep learning model; improving the accuracy of the applied model.

Details

Applied Computing and Informatics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2634-1964

Keywords

Open Access
Article
Publication date: 26 December 2023

Bradley J. Olson, Satyanarayana Parayitam, Matteo Cristofaro, Yongjian Bao and Wenlong Yuan

This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its…

Abstract

Purpose

This paper elucidates the role of anger in error management (EM) and organizational learning behaviors. The study explores how anger can catalyze learning, emphasizing its strategic implications.

Design/methodology/approach

A double-layered moderated-mediated model was developed and tested using data from 744 Chinese CEOs. The psychometric properties of the survey instrument were rigorously examined through structural equation modeling, and hypotheses were tested using Hayes's PROCESS macros.

Findings

The findings reveal that anger is a precursor for recognizing the value of significant errors, leading to a positive association with learning behavior among top management team members. Additionally, the study uncovers a triple interaction effect of anger, EM culture and supply chain disruptions on the value of learning from errors. Extensive experience and positive grieving strengthen the relationship between recognizing value from errors and learning behavior.

Originality/value

This study uniquely integrates affect-cognitive theory and organizational learning theory, examining anger in EM and learning. The authors provide empirical evidence that anger can drive error value recognition and learning. The authors incorporate a more fine-grained approach to leadership when including executive anger as a trigger to learning behavior. Factors like experience and positive grieving are explored, deepening the understanding of emotions in learning. The authors consider both negative and positive emotions to contribute to the complexity of organizational learning.

Details

Management Decision, vol. 62 no. 13
Type: Research Article
ISSN: 0025-1747

Keywords

Open Access
Article
Publication date: 16 July 2020

Rosa Angela Fabio, Sonia Esposito, Cristina Carrozza, Gaetana Pino and Tindara Caprì

Various studies have examined the role of executive functions in autism, but there is a lack of research in the current literature on cognitive flexibility in autism spectrum…

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Abstract

Purpose

Various studies have examined the role of executive functions in autism, but there is a lack of research in the current literature on cognitive flexibility in autism spectrum disorders (ASD). The purpose of this study is to investigate whether cognitive flexibility deficits could be related to facial emotion recognition deficits in ASD.

Design/methodology/approach

In total, 20 children with ASD and 20 typically developing children, matched for intelligence quotient and gender, were examined both in facial emotion recognition tasks and in cognitive flexibility tasks through the dimensional change card sorting task.

Findings

Despite cognitive flexibility not being a core deficit in ASD, impaired cognitive flexibility is evident in the present research. Results show that cognitive flexibility is related to facial emotion recognition and support the hypothesis of an executive specific deficit in children with autism.

Research limitations/implications

One of the limit is the use of just one cognitive test to measure cognitive flexibility and facial recognition. This could be important to be taken into account in the new research. By increasing the number of common variables assessing cognitive flexibility, this will allow for a better comparison between studies to characterize impairment in cognitive flexibility in ASD.

Practical implications

Investigating impairment in cognitive flexibility may help to plan training intervention based on the induction of flexibility.

Social implications

If the authors implement cognitive flexibility people with ASD can have also an effect on their social behavior and overcome the typical and repetitive behaviors that are the hallmark of ASD.

Originality/value

The originality is to relate cognitive flexibility deficits to facial emotion.

Details

Advances in Autism, vol. 6 no. 3
Type: Research Article
ISSN: 2056-3868

Keywords

Open Access
Article
Publication date: 28 April 2023

Desirée H. van Dun and Maneesh Kumar

Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech…

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Abstract

Purpose

Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.

Design/methodology/approach

Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.

Findings

The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.

Originality/value

Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.

Details

International Journal of Operations & Production Management, vol. 43 no. 13
Type: Research Article
ISSN: 0144-3577

Keywords

Open Access
Article
Publication date: 3 July 2017

Leony Derick, Gayane Sedrakyan, Pedro J. Munoz-Merino, Carlos Delgado Kloos and Katrien Verbert

The purpose of this paper is to evaluate four visualizations that represent affective states of students.

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Abstract

Purpose

The purpose of this paper is to evaluate four visualizations that represent affective states of students.

Design/methodology/approach

An empirical-experimental study approach was used to assess the usability of affective state visualizations in a learning context. The first study was conducted with students who had knowledge of visualization techniques (n=10). The insights from this pilot study were used to improve the interpretability and ease of use of the visualizations. The second study was conducted with the improved visualizations with students who had no or limited knowledge of visualization techniques (n=105).

Findings

The results indicate that usability, measured by perceived usefulness and insight, is overall acceptable. However, the findings also suggest that interpretability of some visualizations, in terms of the capability to support emotional awareness, still needs to be improved. The level of students’ awareness of their emotions during learning activities based on the visualization interpretation varied depending on previous knowledge of information visualization techniques. Awareness was found to be high for the most frequently experienced emotions and activities that were the most frustrating, but lower for more complex insights such as interpreting differences with peers. Furthermore, simpler visualizations resulted in better outcomes than more complex techniques.

Originality/value

Detection of affective states of students and visualizations of these states in computer-based learning environments have been proposed to support student awareness and improve learning. However, the evaluation of visualizations of these affective states with students to support awareness in real life settings is an open issue.

Details

Journal of Research in Innovative Teaching & Learning, vol. 10 no. 2
Type: Research Article
ISSN: 2397-7604

Keywords

Open Access
Article
Publication date: 2 September 2021

Steve Lambert, Nikolaos Dimitriadis, Matteo Venerucci and Mike Taylor

The purpose of this viewpoint paper is to explore the fixation of the eyes of human resource (HR) professionals' when identifying emotions in the context of workplace research and…

Abstract

Purpose

The purpose of this viewpoint paper is to explore the fixation of the eyes of human resource (HR) professionals' when identifying emotions in the context of workplace research and to propose measures that might support them in their role.

Design/methodology/approach

This paper combines a contemporary literature review with reflections from practice to develop more nuanced understandings of 39 HR professionals' ability to recognise emotions. This paper used eye-tracking technology more commonly used in laboratory-based students to explore the fixation of the eye when identifying emotions.

Findings

The preliminary findings suggest that HR professionals with higher levels of emotional recognition principally focus on the eyes of the recipient, whereas those with lower levels or emotional recognition focus more so the nose or the randomly across the face, depending on the level of emotional recognition. The data suggest that women are better than men, in the sample group at recognising emotions, with some variations in recognising specific emotions such as disgust.

Research limitations/implications

The viewpoint paper proposes a number of implications for middle leaders and suggests that middle leaders should proactively seek out opportunities to be engaged in activities that support the Default Mode Network (DMN) function of the brain and subsequently the relationship-orientated aspects of leadership, for example, coaching other staff members. However, it has to be recognised that the sample size is small and further work is needed before any generalisations can be made.

Originality/value

This paper offers a contemporary review underpinned by a preliminary study into HR professionals' ability to recognise emotions.

Details

Journal of Work-Applied Management, vol. 14 no. 1
Type: Research Article
ISSN: 2205-2062

Keywords

Open Access
Article
Publication date: 11 July 2023

Miroslav Despotovic, David Koch, Eric Stumpe, Wolfgang A. Brunauer and Matthias Zeppelzauer

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation…

Abstract

Purpose

In this study the authors aim to outline new ways of information extraction for automated valuation models, which in turn would help to increase transparency in valuation procedures and thus contribute to more reliable statements about the value of real estate.

Design/methodology/approach

The authors hypothesize that empirical error in the interpretation and qualitative assessment of visual content can be minimized by collating the assessments of multiple individuals and through use of repeated trials. Motivated by this problem, the authors developed an experimental approach for semi-automatic extraction of qualitative real estate metadata based on Comparative Judgments and Deep Learning. The authors evaluate the feasibility of our approach with the help of Hedonic Models.

Findings

The results show that the collated assessments of qualitative features of interior images show a notable effect on the price models and thus over potential for further research within this paradigm.

Originality/value

To the best of the authors’ knowledge, this is the first approach that combines and collates the subjective ratings of visual features and deep learning for real estate use cases.

Details

Journal of European Real Estate Research, vol. 16 no. 2
Type: Research Article
ISSN: 1753-9269

Keywords

Open Access
Article
Publication date: 3 May 2022

Lorentsa Gkinko and Amany Elbanna

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology…

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Abstract

Purpose

Information Systems research on emotions in relation to using technology largely holds essentialist assumptions about emotions, focuses on negative emotions and treats technology as a token or as a black box, which hinders an in-depth understanding of distinctions in the emotional experience of using artificial intelligence (AI) technology in context. This research focuses on understanding employees' emotional experiences of using an AI chatbot as a specific type of AI system that learns from how it is used and is conversational, displaying a social presence to users. The research questions how and why employees experience emotions when using an AI chatbot, and how these emotions impact its use.

Design/methodology/approach

An interpretive case study approach and an inductive analysis were adopted for this study. Data were collected through interviews, documents review and observation of use.

Findings

The study found that employee appraisals of chatbots were influenced by the form and functional design of the AI chatbot technology and its organisational and social context, resulting in a wider repertoire of appraisals and multiple emotions. In addition to positive and negative emotions, users experienced connection emotions. The findings show that the existence of multiple emotions can encourage continued use of an AI chatbot.

Originality/value

This research extends information systems literature on emotions by focusing on the lived experiences of employees in their actual use of an AI chatbot, while considering its characteristics and its organisational and social context. The findings inform the emerging literature on AI.

1 – 10 of 117