Search results for: emotion identification

Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Lemac Tin

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This paper deals with the lyrical subject of the confessional poetry which is the main part of her stylistic strucuture. We concluded two types of this subject in the classical confessional poetic discourse; reflexive and authentic subject. We offer the model of their genesis, textual features and appeareance realisations. Genesis is related to the theories of deriving poetry from emotion and magic and their similar position in the primitive lyrics and lyrics of the ancient civilizations. Textual features are related to the emotive and semiotic analysis of each type. Appearance realisations of these two types are I-subject, We-subject, transvocal and objectified subject. We check this approaches on some of the poems from World literature.

Keywords: confessional poetry, confessional lyrical subject, magic, emotion, emotive analysis, semiotic analysis

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Liang Zhao, Chong-quan Zhong

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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.

Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation

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Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

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Authors: Mohammadhossein Moghimi, Robert Stone, Pia Rotshtein

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Recording psychological and physiological correlates of human performance within virtual environments and interpreting their impacts on human engagement, ‘immersion’ and related emotional or ‘effective’ states is both academically and technologically challenging. By exposing participants to an effective, real-time (game-like) virtual environment, designed and evaluated in an earlier study, a psychophysiological database containing the EEG, GSR and Heart Rate of 30 male and female gamers, exposed to 10 games, was constructed. Some 174 features were subsequently identified and extracted from a number of windows, with 28 different timing lengths (e.g. 2, 3, 5, etc. seconds). After reducing the number of features to 30, using a feature selection technique, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) methods were subsequently employed for the classification process. The classifiers categorised the psychophysiological database into four effective clusters (defined based on a 3-dimensional space – valence, arousal and dominance) and eight emotion labels (relaxed, content, happy, excited, angry, afraid, sad, and bored). The KNN and SVM classifiers achieved average cross-validation accuracies of 97.01% (±1.3%) and 92.84% (±3.67%), respectively. However, no significant differences were found in the classification process based on effective clusters or emotion labels.

Keywords: virtual reality, effective computing, effective VR, emotion-based effective physiological database

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Authors: Martha Serrano-Arias, Martha Frías-Armenta

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Significant results have been found both supporting universality of emotion recognition and cultural background influence. Thus, the aim of this research was to test a Mexican version of the MTSI in different cultures to find differences in their performance. The MTSI-Mx assesses through a scenario approach were subjects must evaluate real persons. Two target persons were used for the construction, a man (FS) and a woman (AD). The items were grouped in four variables: Picture, Video, and FS and AD scenarios. The test was applied to 201 students from Mexico and Germany. T-test for picture and FS scenario show no significance. Video and AD had a significance at the 5% level. Results show slight differences between cultures, although a more comprehensive research is needed to conclude which culture can perform better in this kind of assessments.

Keywords: emotion recognition, MTSI, social intelligence, transcultural study

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error

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Authors: Darnetty Baharuddin Salleh

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Fusarium ear rot disease is one of the most important diseases of maize and not only causes significant losses but also produced harmful mycotoxins to animals and humans. A total of 141 strains of Fusarium species were isolated from maize plants showing typical ear rot symptoms in Indonesia, and Malaysia by using the semi-selective medium (peptone pentachloronitrobenzene agar, PPA). These strains were identified morphologically. For strains in Gibberella fujikuroi species complex (Gfsc), the identification was continued by using biological identification. Three species of Fusarium were morphologically identified as Fusarium in Gibberella species complex (105 strains, 74.5%), F. verticillioides (78 strains), F. proliferatum (24 strains) and F. subglutinans (3 strains) and five species from other section (36 strains, 25.5%), F. graminearum (14 strains), F. oxysporum (8 strains), F. solani ( 1 strain), and F. semitectum (13 strains). Out of 105 Fusarium species in Gfsc, 63 strains were identified as MAT-1, 25 strains as MAT-2 and 17 strains could not be identified and in crosses with nine standard testers, three mating populations of Fusarium were identified as MP-A, G. moniliformis (68 strains, 64.76%), MP-D, G. intermedia (21 strains, 20%) and MP-E, G. subglutinans (3 strains, 2.9%), and 13 strains (12.38%) could not be identified. All trains biologically identified as MP-A, MP-D, and MP-E, were identified morphologically as F. verticillioides, F. proliferatum, and F. subglutinans, respectively. Thus, the results of this study indicated that identification based on biological identification were consistent with those of morphological identification. This is the first report on the presence of MP-A, MP-D, and MP-E on ear rot-infected maize in Indonesia; MP-A and MP-E in Malaysia.

Keywords: Fusarium, MAT-1, MAT-2, MP-A, MP-D, MP-E

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Authors: Leah Wilck

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Eyewitness identification is arguably one of the most utilized practices within our legal system; however, exoneration cases indicate that this practice may lead to accuracy and conviction errors. The purpose of this study was to examine the effects of the cross-race effect, the phenomena in which people are able to more easily and accurately identify faces from within their racial category, on the accuracy of eyewitness identification. Participants watched three separate videos of a perpetrator trying to steal a bicycle. In each video, the perpetrator was of a different race and gender. Participants watched a video where the perpetrator was a Black male, a White male, and a White female. Following the completion of watching each video, participants were asked to recall everything they could about the perpetrator they witnessed. The initial results of the study did not find the expected cross-race effect impacted the eyewitness identification accuracy. These surprising results are discussed in terms of cross-race bias and recognition theory as well as applied implications.

Keywords: cross race effect, eyewitness identification, own-race bias, racial profiling

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Authors: Beaudoin Marie-Joelle, Poirier Nathalie

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Introduction: Children with autism spectrum disorder (ASD) tend to lack socio-emotional skills (e.g., emotional regulation and theory of mind). Eisenberg’s theoretical model on emotion-related socialization behaviors suggests that mothers of children with ASD could play a central role in fostering the acquisition of socio-emotional skills by engaging in frequent educational conversations about emotions. Although, mothers’ perceptions of their own emotional skills and their child’s personality traits and social deficits could mitigate the benefit of their educative role. Objective: Our study aims to explore the association between mother-child conversations about emotions and the socio-emotional skills of their children when accounting for the moderating role of the mothers’ perceptions. Forty-nine mothers completed five questionnaires about emotionally related conversations, self-openness to emotions, and perceptions of personality and socio-emotional skills of their children with ASD. Results: Regression analyses showed that frequent mother-child conversations about emotions predicted better emotional regulation and theory of mind skills in children with ASD (p < 0.01). The children’s theory of mind was moderated by mothers’ perceptions of their own emotional openness (p < 0.05) and their perceptions of their children’s openness to experience (p < 0.01) and conscientiousness (p < 0.05). Conclusion: Mothers likely play an important role in the socio-emotional education of children with ASD. Further, mothers may be most helpful when they perceive that their interventions improve their child’s behaviors. Our findings corroborate those of the Eisenberg model, which claims that mother-child conversations about emotions predict socio-emotional development skills in children with ASD. Our results also help clarify the moderating role of mothers’ perceptions, which could mitigate their willingness to engage in educational conversations about emotions with their children. Therefore, in special needs' children education, school professionals could collaborate with mothers to increase the frequency of emotion-related conversations in ASD's students with emotion dysregulation or theory of mind problems.

Keywords: autism, parental socialization of emotion, emotional regulation, theory of mind

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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Authors: Michael Subbey, Kwame Takyi Danquah

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Finding a child's exceptional skills and abilities at a young age and nurturing them is a challenging process. The Social Learning Theory (SLT) of Albert Bandura is used to analyze the effects of early talent identification on children's growth and development. The study examines both the advantages and disadvantages of early talent identification and stresses the significance of a moral strategy that puts the welfare of the child first. The paper emphasizes the value of a balanced approach to early talent identification that takes into account individual differences, cultural considerations, and the child's social environment.

Keywords: early talent development, social learning theory, child development, child welfare

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Authors: Joserra Díez, Ainhoa Meñika, Iñaki Sanz-Azkue, Arritokieta Ortuzar

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Biodiversity provides humans with a great range of ecosystemic services; it is therefore an indispensable resource and a legacy to coming generations. However, in the last decades, the increasing exploitation of the Planet has caused a great loss of biodiversity and its acquaintance has decreased remarkably; especially in urbanized areas, due to the decreasing attachment of humans to nature. Yet, the Primary Education curriculum primes the identification of flora and fauna to guarantee the knowledge of children on their surroundings, so that they care for the environment as well as for themselves. In order to produce effective didactic material that meets the needs of both teachers and pupils, it is fundamental to diagnose the current situation. In the present work, the knowledge on biodiversity of 3^rd cycle Primary Education students in Biscay (n=98) and its relation to the size of the town/city of their school is discussed. Two tests have been used with such aim: one for tree identification and the other one so that the students enumerated the species of trees and animals they knew. Results reveal that knowledge of students on tree identification is scarce regardless the size of the city/town and of their school. On the other hand, animal species are better known than tree species.

Keywords: biodiversity, population, tree identification, animal identification

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Authors: Mirela-Gabriela Bratu

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The main objective of this study is to highlight the way in which emotions are constructed discursively in the French written press, more particularly in the titles of informative articles. To achieve this objective, we will begin the study with the theoretical part, which aims to capture the characteristics of journalistic discourse, to which we will add clues of emotions that we will identify in the titles of the articles. The approach is based on the empirical results from the analysis of the articles published on the earthquake that took place on August 24, 2016, in Italy, as described by two French national daily newspapers: Le Monde and Le Point. The corpus submitted to the analysis contains thirty-seven titles, published between August 24, 2016, and August 24, 2017. If the textual content of the speech offers information respecting the grammatical standards and following the presentation conventions, the choice of words can touch the reader, so the journalist must add other means than mastering of the language to create emotion. This study aims to highlight the strategies, such as rhetorical figures, the tenses, or factual data, used by journalists to create emotions for the readers. We also try, thanks to the study of the articles which were published for several days relating to the same event, to emphasize whether we can speak or not of the dissipation of emotion and the catastrophic side as the event fades away in time. The theoretical framework is offered by works on rhetorical strategies (Perelman, 1992; Amossi, 2000; Charaudeau, 2000) and on the study of emotions (Plantin, 1997, 1998, 2004; Tetu, 2004).

Keywords: disaster, earthquake, emotion, feeling

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Authors: Angelina A. Tzacheva, Jaishree Ranganathan

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Interest in (STEM) Science Technology Engineering Mathematics education especially Computer Science education has seen a drastic increase across the country. This fuels effort towards recruiting and admitting a diverse population of students. Thus the changing conditions in terms of the student population, diversity and the expected teaching and learning outcomes give the platform for use of Innovative Teaching models and technologies. It is necessary that these methods adapted should also concentrate on raising quality of such innovations and have positive impact on student learning. Light-Weight Team is an Active Learning Pedagogy, which is considered to be low-stake activity and has very little or no direct impact on student grades. Emotion plays a major role in student’s motivation to learning. In this work we use the student feedback data with emotion classification using surveys at a public research institution in the United States. We use Actionable Pattern Discovery method for this purpose. Actionable patterns are patterns that provide suggestions in the form of rules to help the user achieve better outcomes. The proposed method provides meaningful insight in terms of changes that can be incorporated in the Light-Weight team activities, resources utilized in the course. The results suggest how to enhance student emotions to a more positive state, in particular focuses on the emotions ‘Trust’ and ‘Joy’.

Keywords: actionable pattern discovery, education, emotion, data mining

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Authors: N. Reichbach, A. Kuperman

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The paper describes a design of a monitoring system for super capacitor packs in propulsion systems, allowing determining the instantaneous energy capacity under power loading. The system contains real-time recursive-least-squares identification mechanism, estimating the values of pack capacitance and equivalent series resistance. These values are required for accurate calculation of the state-of-energy.

Keywords: real-time monitoring, RLS identification algorithm, state-of-energy, super capacitor

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Authors: Wang Chung-Kwei, Lo Kuo Ying

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This study is aimed to examine main and moderation effect of Chinese traditional social wisdom ‘Ren-qing Shi-kuo’ on the adjustment of insurance workers. Rationale: Ren-qing Shi-ku as a social wisdom has been emphasized and practiced by collective-oriented Chinese for thousand years. The concept of‘Ren-qing Shi-ku’includes values, beliefs and behavior rituals, which helps Chinese to cope with interpersonal conflicts in a sophisticated and closely tied collective society. Based on interview and literature review, we found out Chinese still emphasized the importance of ‘Ren-qing Shi-ku’. The concepts contains five factors, including ‘proper emotion display’, ‘social ritual abiding’, ‘ make empathetic concession’, ‘harmonious and proper behavior’ and ‘tolerance for the interest of the whole’. We developed an indigenous ‘Ren-qing Shi-ku’scale based on interview data and a survey on social worker students. Research methods: We conduct a dyad survey between 294 insurance worker and their supervisors. Insurance workers’ response on ‘Ren-qing Shi-ku,emotion labor, emotional exhaustion, work stress and load, work satisfaction and well-being were collected. We also ask their supervisors to rate these workers ‘empathy, social rule abiding, work performance, and Ren-qing Shi-ku performance. Results: Students’self-ratings on Ren-qing Shi-ku scale are positively correlated with rating from their supervisors on all above indexes. Workers who have higher Ren-qing Shi-ku score also have lower work stress and emotion exhaustion, higher work satisfaction and well-being, more emotion deep acting. They also have higher work performance, social rule abiding, and Ren-qing Shi-ku performance rating from their supervisor. The finding of this study suggested Ren-qing Shi-ku is an effective indicator on insurance workers ‘adjustment. Since Ren-qing Shi-ku is trainable, we suggested that Ren-qing Shi-ku training might be beneficial to service industry in a collective-oriented culture.

Keywords: work stress, Ren-qing Shi-ku, emotional exhaustion, work satisfaction, well-being

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Authors: Z. Masoumi, B. Moaveni

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This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Kalman filter (KF), least square estimation (LSE), structural health monitoring (SHM), structural system identification

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

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Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple sub-sampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two stage identification approach, using small-sized iris code templates in a pre-selection satge, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification

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Authors: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

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The hospitality sector contributes significantly to the global economy but it is also responsible for imposing adverse influences both environmentally and socially. The objective of this research is two-fold: (1) examining the direct impact of internal CSR and external CSR and indirect impact via organizational identification on creative performance and organizational citizenship behavior (OCB), and (2) determining the moderating role of ethical leadership in the relationships of internal- and external- CSR with organizational identification in a cross-cultural context. The data was were collected using multi-respondents and time-lagged data from 260 Pakistani and 239 UK respondents working in upscale hotels of the United Kingdom and Pakistan. The results demonstrate significant differences in both cultures as external CSR has a more substantial impact on organizational identification in the UK, whereas organizational identification has a relatively stronger influence on OCB and creative performance in collectivistic culture (i.e., Pakistan). The findings also confirmed that ethical leadership significantly moderates the relationship of internal- and external - CSR on organizational identification.

Keywords: Huma Sarwar, Muhammad Ishtiaq Ishaq, Junaid Aftab

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Authors: Liz Jackson

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Fear is usually considered as a basic emotion. In society, it is normally cast as undesirable, but also as partly unavoidable. Fear can be said to underlie courage or be required for courage, or it can be understood as its foil. Fear is not normally promoted (intentionally) in education, or treated as something that should be cultivated in schools or in society. However, fear is a basic, to some extent unavoidable emotion, related to truly fearsome things in the world. Fear is also understood to underlie anxiety. Fear is seen as basically disruptive to education, while from a psychological view it is an ordinary state. that cannot be avoided altogether. Despite calls to diminish this negative and mixed feeling in education and society, it can be regarded as socially and personally valuable, and psychologically functional in some situations. One should not take for granted the goodness of fear. However, it can be productive to explore its moral worth, and uses and abuses. Such uncomfortable feelings and experiences can be cultivated and explored via educational and other societal influences, in ways that can benefit a person and their relations with others in the world, while they can also be detrimental.

Keywords: virtue ethics, philosophy of education, moral philosophy, fear

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Authors: Rubijesmin Abdul Latif, Norshakirah Abdul Aziz, Mohd Taufik Abdul Jalil

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This paper focuses on the impact of online games among Malaysian undergraduate students. The purpose of this study is to investigate whether online games (especially MMOGs) impacted students positively or vice versa; focusing on three elements (time management, social life, and emotion). A total of 83 respondents comprised from 14 Malaysia universities, randomly selected undergraduate students who play MMOGs (casual and hardcore gamers i.e. addiction to MMOGs) were involved in this study. The results showed that MMOGs have only negative impact on students capabilities in time management, meanwhile as for the elements social life and emotion, MMOGs do not affect them negatively.

Keywords: internet game addiction, online games, MMOGs, impact, undergraduate students

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Authors: Jachin Pousson, Valdis Bernhofs

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Applications of the binaural sound experience are wide-ranged. This paper focuses on the interaction between binaural tones and human emotion with an aim to apply the resulting knowledge artistically. For the purpose of this study, binaural music is defined as musical arrangements of sound which are made of combinations of binaural difference tones. Here, the term ‘binaural difference tone’ refers to the pulsating tone heard within the brain which results from listening to slightly differing audio frequencies or pure pitches in each ear. The frequency or tempo of the pulsations is the sum of the precise difference between the frequencies two tones and is measured in beats per second. Polyrhythmic pulsations that can be heard within combinations of these differences tones have shown to be able to entrain or tune brainwave patterns to frequencies which have been linked to mental states which can be characterized by different levels of attention and mood.

Keywords: binaural auditory pulsations, brainwave entrainment, emotion, music composition

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Authors: Anna Wendolowska, Dorota Czyzowska

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An intimate relationship is a significant factor that influences romantic partners’ well-being. In the face of stress, avoidant partners often employ a defense-against-intimacy strategy, leading to reduced relationship satisfaction, intimacy, interdependence, and longevity. Dyadic coping can buffer the negative effects of stress on relational satisfaction. Emotional competence mediates the relationship between insecure attachment and intimacy. In the current study, the link between attachment, different forms of dyadic coping, and various aspects of relationship satisfaction was examined. Both partners completed the attachment style questionnaire, the well matching couple questionnaire, and the dyadic coping inventory. The data was analyzed using the actor–partner interdependence model. The results highlighted a negative association between insecure-avoidant attachment style and intimacy. The actor effects of avoidant attachment on relational intimacy for women and for men were significant, whilst the partner effects for both spouses were not significant. The emotion-focused common dyadic coping moderated the relationship between avoidance of attachment and the partner's sense of intimacy. After controlling for the emotion-focused common dyadic coping, the actor effect of attachment on intimacy for men was slightly weaker, and the actor effect for women turned out to be insignificant. The emotion-focused common dyadic coping weakened the negative association between insecure attachment and relational intimacy. The impact of adult attachment and dyadic coping significantly contributes to subjective relational well-being.

Keywords: adult attachment, dyadic coping, relational intimacy, relationship satisfaction

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Authors: Chloe Shu-Hua Yeh

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Effects of videogame play on players cognitive abilities is a growing research field in the recent decades, however, little is known about how ‘out-of-school’ use of videogame influences creativity. This interdisciplinary research explores the cognitive and emotional effects of two different types of online videogames (an action videogame and a non-action videogame) on subsequent creativity performances using a within-participant design study with 36 participants. Results showed that after playing the action game participants performed higher originality, elaboration and flexibility than after playing the causal game. The results explored effects of emotional states elicited during playing the games suggesting that arousal may be a significant emotional factor which influence subsequent creativity performance. The cognitive and emotional effects of videogame were discussed followed with implications for emotion-creativity-videogame play research, game designers, educational practitioners and parents.

Keywords: attentional breadth, creativity, emotion, videogame play

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: adaptive filtering, sparse system identification, TD-LMS algorithm, VSSLMS algorithm

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Authors: Vinod C. Nayak

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In day-to-day forensic practice, identification is always a difficult task. Availability of anti-mortem and postmortem records plays a major rule in facilitating this tough task. However, the advent of digital forensic is a boon for forensic experts. This study has made use of digital forensics to establish identity by radiological dimensions of maxillary sinus using workstation software. The findings suggest a significant association between maxillary sinus dimensions and human gender. The author will be discussing the methods and results of the study in this e-poster.

Keywords: digital forensics, identification, maxillary sinus, radiology

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

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