• Title/Summary/Keyword: emotion engineering

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Emotion-aware Task Scheduling for Autonomous Vehicles in Software-defined Edge Networks

  • Sun, Mengmeng;Zhang, Lianming;Mei, Jing;Dong, Pingping
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.11
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    • pp.3523-3543
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    • 2022
  • Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

Smart Emotion Management System based on multi-biosignal Analysis using Artificial Intelligence (인공지능을 활용한 다중 생체신호 분석 기반 스마트 감정 관리 시스템)

  • Noh, Ayoung;Kim, Youngjoon;Kim, Hyeong-Su;Kim, Won-Tae
    • Journal of IKEEE
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    • v.21 no.4
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    • pp.397-403
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    • 2017
  • In the modern society, psychological diseases and impulsive crimes due to stress are occurring. In order to reduce the stress, the existing treatment methods consisted of continuous visit counseling to determine the psychological state and prescribe medication or psychotherapy. Although this face-to-face counseling method is effective, it takes much time to determine the state of the patient, and there is a problem of treatment efficiency that is difficult to be continuously managed depending on the individual situation. In this paper, we propose an artificial intelligence emotion management system that emotions of user monitor in real time and induced to a table state. The system measures multiple bio-signals based on the PPG and the GSR sensors, preprocesses the data into appropriate data types, and classifies four typical emotional states such as pleasure, relax, sadness, and horror through the SVM algorithm. We verify that the emotion of the user is guided to a stable state by providing a real-time emotion management service when the classification result is judged to be a negative state such as sadness or fear through experiments.

Development of facial recognition application for automation logging of emotion log (감정로그 자동화 기록을 위한 표정인식 어플리케이션 개발)

  • Shin, Seong-Yoon;Kang, Sun-Kyoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.4
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    • pp.737-743
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    • 2017
  • The intelligent life-log system proposed in this paper is intended to identify and record a myriad of everyday life information as to the occurrence of various events based on when, where, with whom, what and how, that is, a wide variety of contextual information involving person, scene, ages, emotion, relation, state, location, moving route, etc. with a unique tag on each piece of such information and to allow users to get a quick and easy access to such information. Context awareness generates and classifies information on a tag unit basis using the auto-tagging technology and biometrics recognition technology and builds a situation information database. In this paper, we developed an active modeling method and an application that recognizes expressionless and smile expressions using lip lines to automatically record emotion information.

A Novel Method for Modeling Emotional Dimensions using Expansion of Russell's Model (러셀 모델의 확장을 통한 감정차원 모델링 방법 연구)

  • Han, Eui-Hwan;Cha, Hyung-Tai
    • Science of Emotion and Sensibility
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    • v.20 no.1
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    • pp.75-82
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    • 2017
  • We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

The Effects of Unconscious Emotion on Motor Program of Information Processing for Movement Execution (비의식적 정서가 동작수행 정보처리과정 중 운동 프로그램에 미치는 효과)

  • Kim, Jae-Woo
    • The Journal of Korean Institute for Practical Engineering Education
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    • v.1 no.1
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    • pp.91-98
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    • 2009
  • In approach of human-robot interaction, it is importance task in future robot industry to make to robot recognize, express, coping the emotions. The purpose of this study was to examination the effects unconscious positive and negative emotion of information processing of motor program. 13 participants(male=11, female=2) viewed smile-face picture and angry-face picture priming at 10ms level, and then performanced button press, button press and one tennis ball hitting, and button press and two tennis ball hitting task. The results appeared that positive emotion triggered more fast RT than negative emotion in planning complex motor program. Possible explanations for the performance differences depended on emotion are discussed and future research directions were provided.

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Feature Selecting Algorithm Development Based on Physiological Signals for Negative Emotion Recognition (부정감성 인식을 위한 생체신호 기반의 특징 선택 알고리즘 개발)

  • Lee, JeeEun;Yoo, Sun K.
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.8
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    • pp.3925-3932
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    • 2013
  • Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.

Design and Implementation of Location Recommending Services using Personal Emotional Information based on Collaborative Filtering (개인 감성정보를 이용한 협업 필터링 기반 장소 추천 서비스 설계 및 구현)

  • Byun, Jeong;Kim, Dong Keun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.8
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    • pp.1407-1414
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    • 2016
  • In this study, we develop that Location Recommending System using personal emotion information based on Collaborative Filtering. Previous Location Recommending System recommended a place visited by the user of the rating or the pattern of location for the user place. These systems are not high user satisfaction because that dose not consider the user status or have not objectively the information. Using user's personal emotion information to recommend a high-affinity users who have visited the place felt similar emotions objectively can improve user satisfaction with the place. In this study, a user using a mobile application directly register the recognized emotion information using the current position and bio-signal, and using the registered information measuring the similarity of user with a similarity emotion, predicts a preference for the place it is recommended to emotional place. The system consists of a user interface, a database, a recommendation module.

A Study on the Adjectives for Selection of Color Patterns (컬러 패턴 선택을 위한 형용사에 관한 연구)

  • Kim Sung-Hwan;Eum Kyoung-Bae;Chung Sung-Suk;Lee Joon-Whoan
    • Science of Emotion and Sensibility
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    • v.8 no.4
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    • pp.355-363
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    • 2005
  • The adjectives for represnting emotions is important to evaluate and select the colors or color patterns. In this paper, we perform the MDS analysis, factor analysis, and cluster analysis to the Soen's experimental data obtained from the evaluation of random color patterns with 13 adjective pairs. As a result, those adjectives can be reduced 3 different factors representing emotions of weight, activity and temperature, which is approximately corresponds the results of previous researches on single colors. Also, we show that the adjectives for preference can be approximate4 by other primary adjectives for color patterns using regression analysis. This implies that one can construct a uniform emotion space for evaluating and selecting color patterns regardless of objects such as wall papers, carpets, and so on.

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Analysis of Emotions in Broadcast News Using Convolutional Neural Networks (CNN을 활용한 방송 뉴스의 감정 분석)

  • Nam, Youngja
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.8
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    • pp.1064-1070
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    • 2020
  • In Korea, video-based news broadcasters are primarily classified into terrestrial broadcasters, general programming cable broadcasters and YouTube broadcasters. Recently, news broadcasters get subjective while targeting the desired specific audience. This violates normative expectations of impartiality and neutrality on journalism from its audience. This phenomenon may have a negative impact on audience perceptions of issues. This study examined whether broadcast news reporting conveys emotions and if so, how news broadcasters differ according to emotion type. Emotion types were classified into neutrality, happiness, sadness and anger using a convolutional neural network which is a class of deep neural networks. Results showed that news anchors or reporters tend to express their emotions during TV broadcasts regardless of broadcast systems. This study provides the first quantative investigation of emotions in broadcasting news. In addition, this study is the first deep learning-based approach to emotion analysis of broadcasting news.

Design and fabrication of paper microfluidic channel (종이기반 미세유체 채널의 설계 및 제작기술)

  • Lee, Jung-Hyun;Hwang, Yoo-Sun;Jung, Hyo-Il
    • Science of Emotion and Sensibility
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    • v.14 no.4
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    • pp.525-530
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    • 2011
  • Emotion is composed of various feelings such as pleasure, sorrow, comfortability, and so on. The complicated process of the measurement has long been recognized as a major hindrance for the studies of emotion. Previously, individuals' emotion has mainly been measured by means of self-report, interview, EEG (electroencephalogram), ECG (electrocardiogram), EOG (electroculography), and body temperature. With thanks to nano/micro technologies, the possibility in the development of emotion-on-a-chip (EOC) has begun to be proposed. EOC will make it possible to analyze one's psychological status by taking a drop of blood. Discovery of emotional biomarkers in body fluids, understanding of the correlation between those biomarkers and the results from brain science are prerequisites to validate the EOC technology. In this paper, paper microfluidics are introduced as a good candidate for the EOC. As paper microfluidics is cost-effective and easy to use it is expected to be a useful device for the emotion measurement. We present the design and fabrication process for the simple paper-based microfluidic device and discuss the possible application in the field of measuring the human emotion.

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