scholarly journals Automatic detection and classification of emotional states in virtual reality and standard environments (LCD): comparing valence and arousal of induced emotions

2021 ◽  
Author(s):  
Martin Magdin ◽  
Zoltán Balogh ◽  
Jaroslav Reichel ◽  
Jan Francisti ◽  
Štefan Koprda ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Negative Emotion ◽  
Reference Value ◽  
Classification Model ◽  
Control Group ◽  
Emotional States ◽  
Self Assessment ◽  
Valence And Arousal

AbstractThe following case study was carried out on a sample of one experimental and one control group. The participants of the experimental group watched the movie section from the standardized LATEMO-E database via virtual reality (VR) on Oculus Rift S and HTC Vive Pro devices. In the control group, the movie section was displayed on the LCD monitor. The movie section was categorized according to Ekman's and Russell's classification model of evoking an emotional state. The range of valence and arousal was determined in both observed groups. Valence and arousal were measured in each group using a Self-Assessment Manikin (SAM). The control group was captured by a camera and evaluated by Affdex software from Affectiva in order to compare valence values. The control group showed a very high correlation (0.92) between SAM and Affdex results. Having considered the Affdex results as a reference value, it can be concluded that SAM participants evaluated their emotions objectively. The results from both groups show that the movie section is supposed to evoke negative emotion. Negative emotion was perceived more intensely than its counterpart, positive emotion. Using virtual reality to evoke negative emotion (anger) has confirmed that VR triggers a significantly stronger intensity of emotion than LCD.

scholarly journals DECISION TREE C4.5 ALGORITHM FOR TUITION AID GRANT PROGRAM CLASSIFICATION (CASE STUDY: DEPARTMENT OF INFORMATION SYSTEM, UNIVERSITAS TEKNOKRAT INDONESIA)

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heni Sulistiani ◽  
Ahmad Ari Aldino
Keyword(s):  
Decision Tree ◽  
Classification Model ◽  
Grant Program ◽  
C4.5 Algorithm ◽  
Long Time ◽  
The Right ◽  
Short Time ◽  
Tuition Fee

In pandemic era, almost everyone struggles for their life. College students are such example. They have difficulty in paying tuition fee to continue their study. Based on this problematic situation, Universitas Teknokrat Indonesia grants the students who have good academic performance with tuition fee aid program. Many variables used for determining the grant made it hard to make a decision in a short time or even takes very long time. To make it easier for management to decide who is the right student to get grant, it needs classification model. The purpose of this study is the classification of grant recipients by using decision tree C4.5 algorithm. That can determine whether a potential student can be accepted as an awardee or not. Then, the results of the classification are validated with ten-fold cross validation with an accuracy, precision and recall with the score of 87 % for all part. It means the model perform quite well to be implemented into system.

Classification of motor errors to provide real-time feedback for sports coaching in virtual reality — A case study in squats and Tai Chi pushes

2018 ◽  
Vol 76 ◽  
pp. 47-59 ◽  
Author(s):  
Felix Hülsmann ◽  
Jan Philip Göpfert ◽  
Barbara Hammer ◽  
Stefan Kopp ◽  
Mario Botsch
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Tai Chi ◽  
Sports Coaching

EFFECT OF ZEN MEDITATION PRACTICE ON PERCEIVED STRESS IN COLLEGE STUDENTS: A SURVEY STUDY

2007 ◽  
Vol 19 (06) ◽  
pp. 409-413 ◽  
Author(s):  
Pei-Chen Lo ◽  
Shr-Da Wu
Keyword(s):  
College Students ◽  
Perceived Stress ◽  
Negative Emotion ◽  
Emotional Problem ◽  
Survey Study ◽  
Lower Percentage ◽  
Control Group ◽  
Meditation Practice ◽  
Emotional States ◽  
Meditation Experience

Most physical and psychological problems in modern people have been proven to be caused by stress. This finding stimulated the demand for techniques that can effectively manipulate the stress perception. The influence of stress on college students lasts longer at the age when there is a fast development of personality and life viewpoint. This survey study thus mainly examines the effect of Zen-meditation practice on stress manipulation in college students. 541 college students were divided into two groups, with Zen-meditation practice in their daily lives and those who do not meditate. To evaluate the perceived stress of participants, DASS questionnaire was used to measure their negative emotional states (depression, anxiety and stress/tension). The results showed that (1) considerably high percentage of college students who did not practice Zen meditation exhibited negative emotional problem (depression: 45%; anxiety: 48%; stress/tension: 50%); (2) a much lower percentage of students with meditation practice encountered the negative emotional problem (depression: 8%; anxiety: 30%; stress/tension: 12%). This study reflects the benefits of meditation on stress manipulation. It may also imply that having more meditation, having longer meditation time, and doing meditation more frequently could further improve the states of negative emotion. It also implies that meditation experience played a considerable role in effectively manipulating some stress symptoms like depression and anxiety. This is demonstrated by the significantly lower scores (p < 0.001) in the group of experienced (> 0.5 year) meditators as compared with the control group.

Fuzzy Classification of Customer Insolvency in Mobile Telecommunication

2014 ◽  
Vol 6 (3) ◽  
pp. 1-29
Author(s):  
Walid Moudani ◽  
Grace Zaarour ◽  
Félix Mora-Camino
Keyword(s):  
Mathematical Formulation ◽  
Classification Problem ◽  
Customer Behavior ◽  
Fuzzy Classification ◽  
Classification Model ◽  
Mobile Telecommunication ◽  
Telecommunication Companies ◽  
Comparison Of The Results

This paper proposes a predictive model to handle customer insolvency in advance for large mobile telecommunication companies for the purpose of minimizing their losses while preserving an overall satisfaction of the customers which may have important consequences on the quality and on the consume return of the operations. A new mathematical formulation taking into consideration a set of business rules and the satisfaction of the customers is proposed. However, the customer insolvency is defined to be a classification problem since our main purpose is to categorize the customer in one of the two classes: potentially insolvent or potentially solvent. Therefore, a model with precise business prediction using the knowledge discovery and Data Mining techniques on an enormous heterogeneous and noisy data is proposed. A fuzzy approach to evaluate and analyze the customer behavior leading to segment them into groups that provide better understanding of customers is developed. These groups with many other significant variables feed into a classification algorithm based on Rough fuzzy Sets technique to classify the customers. A real case study is considered here, followed by analysis and comparison of the results for the reason to select the best classification model that maximizes the accuracy for insolvent customers and minimizes the error rate in the misclassification of solvent customers.

scholarly journals Association between Emotional Intelligence and Hemispheric Activity Asymmetry

2018 ◽  
Author(s):  
O Razumnikova ◽  
E Khoroshavtseva ◽  
A Yashanina
Keyword(s):  
Emotional Intelligence ◽  
Emotional Reactivity ◽  
Negative Emotion ◽  
Low Frequency ◽  
Hemispheric Dominance ◽  
Emotional States ◽  
Self Assessment ◽  
Posterior Cortex ◽  
The Right ◽  
Delta Oscillations

The relations between the asymmetry of hemispheric activity using the EEG rhythms in resting and both trait emotional intelligence (EI-IPIP) and self-assessment of emotional reactivity on IAPS stimuli were studied in university students. The obtained EEG patterns of power asymmetry in both low-frequency and high-frequency indicate different variants of the hemispheric dominance in the anterior and posterior regions of the brain, depending not only on the valence of induced emotions, but also on selfassessment of perception or expression of emotional states. Total EI was associated with relatively greater left frontal activation on low frequency delta oscillations and on higher beta2 oscillations in posterior cortex. Using EEG mapping positive relations were found between the right hemispheric delta rhythm and emotional reactivity to negative emotive stimuli and between the left hemispheric delta and positive affect. Self-rating of positive to negative emotion during both EI and IAPS stimuli-induced affect testing was more pronounced in the relationships to asymmetry of hemispheric activity than separate traits EI. Keywords: Emotional intelligence traits, self-assessment of emotional reactivity, EEG, hemispheric asymmetry, frequency bands

scholarly journals Listening, Corporeality, Place and Presence

2010 ◽  
pp. 113-127
Author(s):  
Susan Turner
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Film Studies ◽  
Sense Of Presence ◽  
Different Types ◽  
Being There

This chapter considers the role of sound, and more specifically, listening, in creating a sense of presence (of “being there”) in “places” recreated by virtual reality technologies. We first briefly review the treatment of sound in place and presence research. Here we give particular attention to the role of sound in inducing a sense of presence in virtual environments that immerse their users in representations of particular places. We then consider the phenomenology of listening, the nature of different types of listening, and their application: listening is active, directed, intentional hearing, and is not merely egocentric, it is body-centric. A classification of modes of listening that draws on work in film studies, virtual reality, and audiology is then proposed as a means of supporting the design of place-centric virtual environments in providing an effective aural experience. Finally, we apply this to a case study of listening in real and simulated soundscapes, and suggest directions for further applications of this work

scholarly journals Interpreting BERT-based stance classification: a case study about the Brazilian COVID vaccination

2021 ◽  
Author(s):  
Carlos Abel Córdova Sáenz ◽  
Karin Becker
Keyword(s):  
Social Distance ◽  
Classification Model ◽  
Correct Classification ◽  
Intrinsic Properties ◽  
Word Attention ◽  
Scientific Facts

The actions to control the COVID-19 pandemics should be based on scientific facts. However, Brazil is facing a politically polarized scenario that has influenced the population’s behavior regarding social distance or vaccination issues. This paper addresses this subject by proposing a BERT-based stance classification model and an attention-based mechanism to identify the influential words for stance classification. The interpretation mechanism traces tokens’ attentions back to words, assigning word attention scores (absolute and relative). We use these metrics to assess if words with high attention weights correspond to domain intrinsic properties and contribute to the correct classification of stances. Our experiments revealed good results for stance classification (F1=0.752), and that 74% of the top-100 words with the highest absolute attention are representative of the arguments that support the investigated stances.

scholarly journals Modelling the Accessibility Classification of Railway Lines: A case study of Northeast China railway network

2013 ◽  
Vol 25 (5) ◽  
pp. 467-474 ◽  
Author(s):  
Mian Yang ◽  
Y.J. Wang
Keyword(s):  
Northeast China ◽  
Decision Support Tool ◽  
Strategic Decision ◽  
Classification Model ◽  
Railway Network ◽  
Support Tool ◽  
China Railway

A major problem addressed in railway network planning relates to distinguishing the role of the railway line in the network, and making a reasonable classification of the lines based on their role. Accessibility has been widely used to measure the role of transportation infrastructure in various studies, but few quantitative models for the classification of the role have been presented yet. In this paper, the line accessibility classification model is proposed, which aims to distinguish the role of railway lines in the network and to classify the lines into different grades. The practicability of the model is demonstrated through the case study of Northeast China railway network where the railway lines in Northeast China can be classified into three grades. The line accessibility classification model is supposed to be a strategic decision support tool for planners and policy makers to determine the classification of railway lines.

Emotional complexity across the life story: Diminished positive emodiversity and elevated negative emodiversity in sufferers of chronic depression

2018 ◽  
Author(s):  
Aliza Werner-Seidler ◽  
Caitlin Hitchcock ◽  
Emily Hammond ◽  
Emma Travers-Hill ◽  
Ann-Marie Golden ◽  
...  
Keyword(s):  
Positive Emotion ◽  
Positive Emotions ◽  
Prolonged Exposure ◽  
Life Story ◽  
Negative Emotion ◽  
Clinical Depression ◽  
Control Group ◽  
Emotional States ◽  
Treatment Resistant ◽  
The Relationship

Greater diversity in the experience of negative and positive emotion – emodiversity - is associated with better mental health outcomes in the general population (Quoidbach et al. 2014). However, conceptual accounts of clinical depression suggest that extensive and prolonged exposure to negative emotional states might actually be reflected in enhanced diversity across negative emotion experiences. Conversely, the opportunity to experience a myriad of varied positive emotions is likely to be reduced in depression, given existing deficits in positive affective experience associated with the disorder. In this study, the diversity of negative and positive emotion experiences in a treatment-resistant chronically depressed sample and a never-depressed control group were compared. We hypothesized that depressed individuals (n=22) would show enhanced emodiversity in the negative emotion domain but reduced emodiversity in the positive domain, relative to the control group (n=20). Results supported these hypotheses. Analyses also showed that among those with depression, reduced positive emodiversity was associated with disorder chronicity, such that both length of time depressed and frequency of past episodes were linked to reduced positive emodiversity. No support was found for an association between negative emotion diversity and depression chronicity. This study provides the first investigation into the relationship between clinical depression and emodiversity, and suggests that supporting depressed individuals to experience a range of diverse positive emotions could be a valuable therapeutic target.

Effect of Emotions in a Lexical Decision Task

2017 ◽  
Vol 76 (2) ◽  
pp. 71-79 ◽  
Author(s):  
Hélène Maire ◽  
Renaud Brochard ◽  
Jean-Luc Kop ◽  
Vivien Dioux ◽  
Daniel Zagar
Keyword(s):  
Lexical Decision ◽  
Lexical Decision Task ◽  
Emotional State ◽  
Control Group ◽  
Decision Task ◽  
Attentional Orienting ◽  
Emotional States ◽  
Sequence Effect ◽  
Emotion Induction ◽  
Before And After

Abstract. This study measured the effect of emotional states on lexical decision task performance and investigated which underlying components (physiological, attentional orienting, executive, lexical, and/or strategic) are affected. We did this by assessing participants’ performance on a lexical decision task, which they completed before and after an emotional state induction task. The sequence effect, usually produced when participants repeat a task, was significantly smaller in participants who had received one of the three emotion inductions (happiness, sadness, embarrassment) than in control group participants (neutral induction). Using the diffusion model ( Ratcliff, 1978 ) to resolve the data into meaningful parameters that correspond to specific psychological components, we found that emotion induction only modulated the parameter reflecting the physiological and/or attentional orienting components, whereas the executive, lexical, and strategic components were not altered. These results suggest that emotional states have an impact on the low-level mechanisms underlying mental chronometric tasks.

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