Surprise: a Belief Or an Emotion? in V.S
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Expectancy and Musical Emotion Effects of Pitch and Timing
Manuscript Expectancy and musical emotion Effects of pitch and timing expectancy on musical emotion Sauvé, S. A.1, Sayed, A.1, Dean, R. T.2, Pearce, M. T.1 1Queen Mary, University of London 2Western Sydney University Author Note Correspondence can be addressed to Sarah Sauvé at [email protected] School of Electronic Engineering and Computer Science Queen Mary University of London, Mile End Road London E1 4NS United Kingdom +447733661107 Biographies S Sauve: Originally a pianist, Sarah is now a PhD candidate in the Electronic Engineering and Computer Science department at Queen Mary University of London studying expectancy and stream segregation, supported by a college studentship. EXPECTANCY AND MUSICAL EMOTION 2 A Sayed: Aminah completed her MSc in Computer Science at Queen Mary University of London, specializing in multimedia. R.T. Dean: Roger is a composer/improviser and researcher at the MARCS Institute for Brain, Behaviour and Development. His research focuses on music cognition and music computation, both analytic and generative. M.T. Pearce: Marcus is Senior Lecturer at Queen Mary University of London, director of the Music Cognition and EEG Labs and co-director of the Centre for Mind in Society. His research interests cover computational, psychological and neuroscientific aspects of music cognition, with a particular focus on dynamic, predictive processing of melodic, rhythmic and harmonic structure, and its impact on emotional and aesthetic experience. He is the author of the IDyOM model of auditory expectation based on statistical learning and probabilistic prediction. EXPECTANCY AND MUSICAL EMOTION 3 Abstract Pitch and timing information work hand in hand to create a coherent piece of music; but what happens when this information goes against the norm? Relationships between musical expectancy and emotional responses were investigated in a study conducted with 40 participants: 20 musicians and 20 non-musicians. -
The Constitution and Revenge Porn
Pace Law Review Volume 35 Issue 1 Fall 2014 Article 8 Symposium: Social Media and Social Justice September 2014 The Constitution and Revenge Porn John A. Humbach Pace University School of Law, [email protected] Follow this and additional works at: https://digitalcommons.pace.edu/plr Part of the Constitutional Law Commons, Criminal Law Commons, First Amendment Commons, Internet Law Commons, Law and Society Commons, and the Legal Remedies Commons Recommended Citation John A. Humbach, The Constitution and Revenge Porn, 35 Pace L. Rev. 215 (2014) Available at: https://digitalcommons.pace.edu/plr/vol35/iss1/8 This Article is brought to you for free and open access by the School of Law at DigitalCommons@Pace. It has been accepted for inclusion in Pace Law Review by an authorized administrator of DigitalCommons@Pace. For more information, please contact [email protected]. The Constitution and Revenge Porn John A. Humbach* “Many are those who must endure speech they do not like, but that is a necessary cost of freedom.”1 Revenge porn refers to sexually explicit photos and videos that are posted online or otherwise disseminated without the consent of the persons shown, generally in retaliation for a romantic rebuff.2 The problem of revenge porn seems to have emerged fairly recently,3 no doubt facilitated by the widespread practice of sexting.4 In sexting, people make and send explicit pictures of themselves using digital devices.5 These devices, in their very nature, permit the pictures to be easily shared with the entire online world. Although the move from sexting to revenge porn might seem as inevitable as the shifting winds * Professor of Law at Pace University School of Law. -
DOCUMENT RESUME Dimensions of Interest and Boredom In
DOCUMENT RESUME ED 397 840 IR 018 028 AUTHOR Small, Ruth V., And Others TITLE Dimensions of Interest and Boredom in Instructional Situations. PUB DATE 96 NOTE 16p.; In: Prbceedings of Selected Research and Development Presentations at the 1996 National Convention of the Association for Educational Communications and Technology (18th, Indianapolis, IN, 1996); see IR 017 960. PUB TYPE Reports Research/Technical (143) Speeches/Conference Papers (150) EDRS PRICE MF01/PC01 Plus Postage. DESCRIPTORS *Academic Achievement; Brainstorming; Cognitive Style; College Students; Educational Strategies; Higher Education; Instructional Development; *Instructional Effectiveness; Instructional Material Evaluation; *Learning Strategies; Likert Scales; Participant Satisfaction; Questionnaires; Relevance (Education); *Stimulation; Student Attitudes; *Student Motivation; Teacher Role; Teaching Methods IDENTIFIERS ARCS Model; *Boredom; Emotions ABSTRACT Stimulating interest and reducing boredom are important goals for promoting learning achievement. This paper reviews previous research on interest and boredom in educational settings and examines their relationship to the characteristics of emotion. It also describes research which seeks to develop a model of learner interest by identifying sources of "boring" and "interesting" leaming situations through analysis of learners' descriptions. Participants is, the study were 512 undergraduate and graduate students from two universities. Descriptive responses were elicited from 350 students through brainstorming -
Applying a Discrete Emotion Perspective
AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIVE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER Bachelor of Science in Psychology Ashland University May 2015 Submitted in partial fulfillment of requirements for the degree MASTER OF ARTS IN PSYCHOLOGY At the CLEVELAND STATE UNIVERSITY May 2019 We hereby approve this thesis For SARA E. LAUTZENHISER Candidate for the Master of Arts in Experimental Research Psychology For the Department of Psychology And CLEVELAND STATE UNIVERSITY’S College of Graduate Studies by __________________________ Eric Allard, Ph.D. __________________________ Department & Date __________________________ Andrew Slifkin, Ph. D. (Methodologist) __________________________ Department & Date __________________________ Conor McLennan, Ph.D. __________________________ Department & Date __________________________ Robert Hurley, Ph. D. __________________________ Department & Date Student’s Date of Defense May 10, 2019 AROUSAL OR RELEVANCE? APPLYING A DISCRETE EMOTION PERSPECTIE TO AGING AND AFFECT REGULATION SARA E. LAUTZENHISER ABSTRACT While research in the psychology of human aging suggests that older adults are quite adept at managing negative affect, emotion regulation efficacy may depend on the discrete emotion elicited. For instance, prior research suggests older adults are more effective at dealing with emotional states that are more age-relevant/useful and lower in intensity (i.e., sadness) relative to less relevant/useful or more intense (i.e., anger). The goal of the present study was to probe this discrete emotions perspective further by addressing the relevance/intensity distinction within a broader set of negative affective states (i.e., fear and disgust, along with anger and sadness). Results revealed that participants reported relatively high levels of the intended emotion for each video, while also demonstrating significant affective recovery after the attentional refocusing task. -
About Emotions There Are 8 Primary Emotions. You Are Born with These
About Emotions There are 8 primary emotions. You are born with these emotions wired into your brain. That wiring causes your body to react in certain ways and for you to have certain urges when the emotion arises. Here is a list of primary emotions: Eight Primary Emotions Anger: fury, outrage, wrath, irritability, hostility, resentment and violence. Sadness: grief, sorrow, gloom, melancholy, despair, loneliness, and depression. Fear: anxiety, apprehension, nervousness, dread, fright, and panic. Joy: enjoyment, happiness, relief, bliss, delight, pride, thrill, and ecstasy. Interest: acceptance, friendliness, trust, kindness, affection, love, and devotion. Surprise: shock, astonishment, amazement, astound, and wonder. Disgust: contempt, disdain, scorn, aversion, distaste, and revulsion. Shame: guilt, embarrassment, chagrin, remorse, regret, and contrition. All other emotions are made up by combining these basic 8 emotions. Sometimes we have secondary emotions, an emotional reaction to an emotion. We learn these. Some examples of these are: o Feeling shame when you get angry. o Feeling angry when you have a shame response (e.g., hurt feelings). o Feeling fear when you get angry (maybe you’ve been punished for anger). There are many more. These are NOT wired into our bodies and brains, but are learned from our families, our culture, and others. When you have a secondary emotion, the key is to figure out what the primary emotion, the feeling at the root of your reaction is, so that you can take an action that is most helpful. . -
Characteristics of the Regulation of the Surprise Emotion Chuanlin Zhu1, Ping Li2, Zhao Zhang2, Dianzhi Liu1 & Wenbo Luo2,3
www.nature.com/scientificreports OPEN Characteristics of the regulation of the surprise emotion Chuanlin Zhu1, Ping Li2, Zhao Zhang2, Dianzhi Liu1 & Wenbo Luo2,3 This study aimed to assess the characteristics of the regulation of the emotion of surprise. Event-related Received: 27 June 2017 potentials (ERPs) of college students when using cognitive reappraisal and expressive suppression to Accepted: 11 April 2019 regulate their surprise level were recorded. Diferent contexts were presented to participants, followed Published: xx xx xxxx by the image of surprised facial expression; subsequently, using a 9-point scale, participants were asked to rate the intensity of their emotional experience. The behavioral results suggest that individuals’ surprise level could be reduced by using both expressive suppression and cognitive reappraisal, in basic and complex conditions. The ERP results showed that (1) the N170 amplitudes were larger in complex than basic contexts, and those elicited by using expressive suppression and cognitive reappraisal showed no signifcant diferences, suggesting that emotion regulation did not occur at this stage; (2) the LPC amplitudes elicited by using cognitive reappraisal and expressive suppression were smaller than those elicited by free viewing in both context conditions, suggesting that the late stage of individuals’ processing of surprised faces was infuenced by emotion regulation. This study found that conscious emotional regulation occurred in the late stages when individuals processed surprise, and the regulation efects of cognitive reappraisal and expressive suppression were equivalent. When we pass an important test, some of us dance out of excitement; when we are informed about the sudden death of a loved one, we feel extremely sad. -
Probabilistic Models of Expectation Violation Predict Psychophysiological Emotional Responses to Live Concert Music
Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music Hauke Egermann, Marcus T. Pearce, Geraint A. Wiggins & Stephen McAdams Cognitive, Affective, & Behavioral Neuroscience ISSN 1530-7026 Cogn Affect Behav Neurosci DOI 10.3758/s13415-013-0161-y 1 23 Your article is protected by copyright and all rights are held exclusively by Psychonomic Society, Inc.. This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Cogn Affect Behav Neurosci DOI 10.3758/s13415-013-0161-y Probabilistic models of expectation violation predict psychophysiological emotional responses to live concert music Hauke Egermann & Marcus T. Pearce & Geraint A. Wiggins & Stephen McAdams # Psychonomic Society, Inc. 2013 Abstract We present the results of a study testing the often- emotion induction, leading to a further understanding of the theorized role of musical expectations in inducing listeners’ frequently experienced emotional effects of music. emotions in a live flute concert experiment with 50 participants. Using an audience response system developed for this purpose, Keywords Emotion . -
Emotion Classification Based on Biophysical Signals and Machine Learning Techniques
S S symmetry Article Emotion Classification Based on Biophysical Signals and Machine Learning Techniques Oana Bălan 1,* , Gabriela Moise 2 , Livia Petrescu 3 , Alin Moldoveanu 1 , Marius Leordeanu 1 and Florica Moldoveanu 1 1 Faculty of Automatic Control and Computers, University POLITEHNICA of Bucharest, Bucharest 060042, Romania; [email protected] (A.M.); [email protected] (M.L.); fl[email protected] (F.M.) 2 Department of Computer Science, Information Technology, Mathematics and Physics (ITIMF), Petroleum-Gas University of Ploiesti, Ploiesti 100680, Romania; [email protected] 3 Faculty of Biology, University of Bucharest, Bucharest 030014, Romania; [email protected] * Correspondence: [email protected]; Tel.: +40722276571 Received: 12 November 2019; Accepted: 18 December 2019; Published: 20 December 2019 Abstract: Emotions constitute an indispensable component of our everyday life. They consist of conscious mental reactions towards objects or situations and are associated with various physiological, behavioral, and cognitive changes. In this paper, we propose a comparative analysis between different machine learning and deep learning techniques, with and without feature selection, for binarily classifying the six basic emotions, namely anger, disgust, fear, joy, sadness, and surprise, into two symmetrical categorical classes (emotion and no emotion), using the physiological recordings and subjective ratings of valence, arousal, and dominance from the DEAP (Dataset for Emotion Analysis using EEG, Physiological and Video Signals) database. The results showed that the maximum classification accuracies for each emotion were: anger: 98.02%, joy:100%, surprise: 96%, disgust: 95%, fear: 90.75%, and sadness: 90.08%. In the case of four emotions (anger, disgust, fear, and sadness), the classification accuracies were higher without feature selection. -
Ambiguous Loss: a Phenomenological
CORE Metadata, citation and similar papers at core.ac.uk Provided by SHAREOK repository AMBIGUOUS LOSS: A PHENOMENOLOGICAL EXPLORATION OF WOMEN SEEKING SUPPORT FOLLOWING MISCARRIAGE By KATHLEEN MCGEE Bachelor of Science in Human Development and Family Science Oklahoma State University Stillwater, Oklahoma 2011 Submitted to the Faculty of the Graduate College of the Oklahoma State University in partial fulfillment of the requirements for the Degree of MASTER OF SCIENCE May, 2014 AMBIGIOUS LOSS: A PHENOMENOLOGICAL EXPLORATION OF WOMEN SEEKING SUPPORT FOLLOWING MISCARRIAGE Thesis Approved: Dr. Kami Gallus Dr. Amanda Harrist Dr. Karina Shreffler ii Name: KATHLEEN MCGEE Date of Degree: MAY, 2014 Title of Study: AMBIGUOUS LOSS: A PHENOMENOLOGICAL EXPLORATION OF WOMEN SEEKING SUPPORT FOLLOWING MISCARRIAGE Major Field: HUMAN DEVELOPMENT AND FAMILY SCIENCE Abstract: Miscarriage is a fairly common experience that is overlooked by today’s society. Miscarriage as simply a female medical issue does not embody the full emotional toll of the experience. Research is lacking on miscarriage and the couple relationship. Even further, a framework for understanding miscarriage is nonexistent. This study aims to explore the phenomenon of miscarriage as well as provide a framework for understanding miscarriage. The current study will look at miscarriage through the lenses of ambiguous loss theory and trauma theory. The sample consisted of 10 females, five who interviewed as individuals and 5 who interviewed with their partners as a couple. Semi-structured, open-ended interviews were conducted with each individual participant, and the five couples were interviewed as a couple as well. From the data, six themes and four subthemes emerged for the female experience: Emotional toll, Stolen dreams, No one understands, He loves me in a different way, Why? I don’t understand, and In the end, I have my faith. -
Revenge Porn and Tort Remedies for Public Figures
William & Mary Journal of Race, Gender, and Social Justice Volume 24 (2017-2018) Issue 1 William & Mary Journal of Women and the Law: 2017 Special Issue: Enhancing Article 9 Women's Effect on Law Enforcement in the Age of Police and Protest November 2017 When Fame Takes Away the Right to Privacy in One's Body: Revenge Porn and Tort Remedies for Public Figures Caroline Drinnon Follow this and additional works at: https://scholarship.law.wm.edu/wmjowl Part of the Law and Gender Commons, Privacy Law Commons, and the Torts Commons Repository Citation Caroline Drinnon, When Fame Takes Away the Right to Privacy in One's Body: Revenge Porn and Tort Remedies for Public Figures, 24 Wm. & Mary J. Women & L. 209 (2017), https://scholarship.law.wm.edu/wmjowl/vol24/iss1/9 Copyright c 2017 by the authors. This article is brought to you by the William & Mary Law School Scholarship Repository. https://scholarship.law.wm.edu/wmjowl WHEN FAME TAKES AWAY THE RIGHT TO PRIVACY IN ONE’S BODY: REVENGE PORN AND TORT REMEDIES FOR PUBLIC FIGURES INTRODUCTION I. A COMMON PHENOMENON—EXAMPLES OF INVASION OF PRIVACY OF PUBLIC FIGURES A. Harms Suffered by Victims of the Distribution of Nonconsensual Pornography B. Legal Remedies Imposed in the “Celebgate” Hacking and Leak Incident II. CIVIL REMEDIES FOR NON–PUBLIC FIGURE VICTIMS OF REVENGE PORN A. Intentional Infliction of Emotional Distress B. Invasion of Privacy Based on Public Disclosure of Private Facts III. HISTORY OF DENYING PRIVACY REMEDIES FOR PUBLIC FIGURES A. What Is a “Public Figure”? B. Distinction Between Public and Private Figures in Privacy-Related Causes of Actions C. -
Association Between Neuroticism and Risk of Incident Cardiovascular Disease in the UK Biobank Cohort
Association between neuroticism and risk of incident cardiovascular disease in the UK Biobank cohort Master Degree Project in Systems Biology Two years Level, 120 ECTS Submitted by: Hira Shahid Email: [email protected] Supervisor: Helgi Schioth Co.supervisor: Gull Rukh Examiner: Diana Tilevik Master Degree Project in Systems Biology Abstract Myocardial infarction (MI) and stroke are the major causes of cardiovascular related morbidities and mortalities around the world. The prevalence of cardiovascular diseases has been increased in last decades and it is vital need of time to investigate this global problem with focus on risk population stratification. The aim of the present study is to investigate the association between individualized personality trait that is neuroticism and risk of MI and stroke has been investigated in a large population-based cohort of UK biobank.375,713 individuals (mean age: 56.24 ± 8.06) were investigated in this longitudinal study and were followed up for seven years to assess the association between neuroticism and risk of MI and stroke incidence. The neuroticism score was assessed by a 12-item questionnaire at baseline, while information related to MI and stroke events was either collected from hospital records and death registries or was self-reported by the participants. Cox proportional hazard regression adjusted for age, gender, BMI, socioeconomic status, lifestyle factors and medical histories for hypertension, diabetes and depression was used. All statistical analyses were performed using R software. In fully adjusted model, a one standard deviation increase in neuroticism score was associated with 1.05-fold increased risk for MI. (HR=1.047(1.009-1.087), p=0.015). -
EMOTION CLASSIFICATION of COVERED FACES 1 WHO CAN READ YOUR FACIAL EXPRESSION? a Comparison of Humans and Machine Learning Class
journal name manuscript No. (will be inserted by the editor) 1 A Comparison of Humans and Machine Learning 2 Classifiers Detecting Emotion from Faces of People 3 with Different Coverings 4 Harisu Abdullahi Shehu · Will N. 5 Browne · Hedwig Eisenbarth 6 7 Received: 9th August 2021 / Accepted: date 8 Abstract Partial face coverings such as sunglasses and face masks uninten- 9 tionally obscure facial expressions, causing a loss of accuracy when humans 10 and computer systems attempt to categorise emotion. Experimental Psychol- 11 ogy would benefit from understanding how computational systems differ from 12 humans when categorising emotions as automated recognition systems become 13 available. We investigated the impact of sunglasses and different face masks on 14 the ability to categorize emotional facial expressions in humans and computer 15 systems to directly compare accuracy in a naturalistic context. Computer sys- 16 tems, represented by the VGG19 deep learning algorithm, and humans assessed 17 images of people with varying emotional facial expressions and with four dif- 18 ferent types of coverings, i.e. unmasked, with a mask covering lower-face, a 19 partial mask with transparent mouth window, and with sunglasses. Further- Harisu Abdullahi Shehu (Corresponding author) School of Engineering and Computer Science, Victoria University of Wellington, 6012 Wellington E-mail: [email protected] ORCID: 0000-0002-9689-3290 Will N. Browne School of Electrical Engineering and Robotics, Queensland University of Technology, Bris- bane QLD 4000, Australia Tel: +61 45 2468 148 E-mail: [email protected] ORCID: 0000-0001-8979-2224 Hedwig Eisenbarth School of Psychology, Victoria University of Wellington, 6012 Wellington Tel: +64 4 463 9541 E-mail: [email protected] ORCID: 0000-0002-0521-2630 2 Shehu H.