Design of Emotional Interaction System Based on Affective Computing Model

2012 ◽  
Vol 198-199 ◽  
pp. 367-373
Author(s):  
Guo Liang Yang ◽  
Jin Hui Zhang ◽  
Hui Sun
Keyword(s):  
Emotional Expression ◽  
Affective Computing ◽  
Quantitative Relationship ◽  
Emotional Information ◽  
Computing Model ◽  
Software Interface ◽  
Emotional Interaction ◽  
Interaction System ◽  
Emotional Model ◽  
Relationship Of

An emotional interaction system is designed by using the theories about affective computing in this paper, which includes the emotional information capturing, machine emotional model and emotional expression. This paper focuses on the problem of building machine emotional model, not only gives the basic definitions of personality space, mood space, and emotion space, but also establishes the quantitative relationship of personality mood and emotion. At last, this paper builds a machine affective model which can reflect the transformation law of the mood, emotion and personality. Related simulation results show that the model can effectively simulates the change law of human emotion. Finally, this paper designs the software interface of the emotional interaction system.

Quantitative relationship of pre-existing antibodies to the excretion of attenuated poliovirus

1964 ◽  
Vol 65 (6) ◽  
pp. 1103
Author(s):  
William Paul Glezen ◽  
George A. Lamb ◽  
Tom D.Y. Chin ◽  
Herbert A. Wenner
Keyword(s):  
Quantitative Relationship ◽  
Relationship Of

RESOURCE UTILIZATION BY THE SOUTHERN PINE BEETLE, DENDROCTONUS FRONTALIS (COLEOPTERA: SCOLYTIDAE)

1976 ◽  
Vol 108 (4) ◽  
pp. 353-362 ◽  
Author(s):  
Robert N. Coulson ◽  
Adil M. Mayyasi ◽  
J. L. Foltz ◽  
F. P. Hain ◽  
W. C. Martin
Keyword(s):  
Pinus Taeda ◽  
Resource Utilization ◽  
Loblolly Pine ◽  
Quantitative Relationship ◽  
Dendroctonus Frontalis ◽  
Adult Density ◽  
Pine Beetle ◽  
Basal Portion ◽  
Relationship Of ◽  
The Relationship

AbstractThe process of resource utilization by Dendroctonus frontalis Zimmerman attacking loblolly pine, Pinus taeda L., was investigated. The quantitative relationship of attacking parent adult D. frontalis as a function of the normalized infested bole height is described by the model y = Ax(1−x)eBx. Greatest attack density occurs at the mid-bole of the tree and tapers toward the top and bottom. Gallery length (and hence eggs)/100 cm2 was independent of attack density. The relationship between gallery length (or eggs) per parent adult and parent adult density is described by the exponential decay curve y = AeBx, indicating that gallery length and egg population density are controlled by a density dependent compensatory feedback process operating instantaneously. Further support for the mechanism was obtained by analyzing the gallery length per parent adult at different locations on the infested bole. The relationship is described by the model y = [AeBx]/[x(1−x)] and indicates that gallery construction and egg population per attacking beetle increase in the upper and basal portion of the bole. The result is a uniform amount of food and space per individual of the developing population.

scholarly journals S-N Curve and Quantitative Relationship of Single-Spot and Multi-Spot Weldings

2020 ◽  
Vol 19 (3) ◽  
pp. 482-493
Author(s):  
L. Yang ◽  
B. Yang ◽  
G. W. Yang ◽  
S. N. Xiao ◽  
T. Zhu ◽  
...  
Keyword(s):  
Quantitative Relationship ◽  
Single Spot ◽  
Relationship Of

scholarly journals QUANTITATIVE RELATIONSHIP OF ELECTRONIC STRUCTURE AND INHIBITION ACTIVITY OF CURCUMIN ANALOGS ON ETHOXYRESORUFIN o-DEALKYLATION (EROD) REACTION

2010 ◽  
Vol 7 (1) ◽  
pp. 78-82
Author(s):  
Harno Dwi Pranowo ◽  
Iqmal Tahir ◽  
Ajidarma Widiatmoko
Keyword(s):  
Electronic Structure ◽  
Statistical Parameter ◽  
Quantitative Relationship ◽  
Equation Model ◽  
Semiempirical Methods ◽  
Inhibition Activity ◽  
Net Charge ◽  
Curcumin Analogs ◽  
Leave One Out ◽  
Relationship Of

Electronic structure and inhibition activity relationship study of curcumin analogs has been established for 29 curcumin analogs on Ethoxyresorufin O-Dealkylation (EROD) reaction using atomic net charge descriptor based on AM1 semiempirical calculations. The QSAR (Quantitative Structure and Activities Relationships) equation model was determined by statistical parameter from multiple regression analysis and leave-one-out cross validation method. The best QSAR equation was described:   Keywords: curcumin, QSAR, descriptor, atomic net charge, semiempirical methods.

Adapting Chatterbots’ Interaction for Use in Children’s Education

2014 ◽  
pp. 413-428
Author(s):  
Antonio F. L. Jacob ◽  
Eulália C. da Mata ◽  
Ádamo L. Santana ◽  
Carlos R. L. Francês ◽  
João C. W. A. Costa ◽  
...  
Keyword(s):  
Knowledge Base ◽  
Affective Computing ◽  
Traditional Methods ◽  
Children's Education ◽  
Computing Model ◽  
Wide Range ◽  
Children’S Education ◽  
Effective Use ◽  
The Web

The Web is providing greater freedom for users to create and obtain information in a more dynamic and appropriate way. One means of obtaining information on this platform, which complements or replaces other forms, is the use of conversation robots or Chatterbots. Several factors must be taken into account for the effective use of this technology; the first of which is the need to employ a team of professionals from various fields to build the knowledge base of the system and be provided with a wide range of responses, i.e. interactions. It is a multidisciplinary task to ensure that the use of this system can be targeted to children. In this context, this chapter carries out a study of the technology of Chatterbots and shows some of the changes that have been implemented for the effective use of this technology for children. It also highlights the need for a shift away from traditional methods of interaction so that an affective computing model can be implemented.

scholarly journals Ensemble Deep Learning for Multilabel Binary Classification of User-Generated Content

Algorithms ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 83 ◽  
Author(s):  
Giannis Haralabopoulos ◽  
Ioannis Anagnostopoulos ◽  
Derek McAuley
Keyword(s):  
Deep Learning ◽  
Sentiment Analysis ◽  
Ensemble Learning ◽  
Affective Computing ◽  
Binary Classification ◽  
User Generated Content ◽  
Emotional Information ◽  
Multiple Classifiers ◽  
Different Levels

Sentiment analysis usually refers to the analysis of human-generated content via a polarity filter. Affective computing deals with the exact emotions conveyed through information. Emotional information most frequently cannot be accurately described by a single emotion class. Multilabel classifiers can categorize human-generated content in multiple emotional classes. Ensemble learning can improve the statistical, computational and representation aspects of such classifiers. We present a baseline stacked ensemble and propose a weighted ensemble. Our proposed weighted ensemble can use multiple classifiers to improve classification results without hyperparameter tuning or data overfitting. We evaluate our ensemble models with two datasets. The first dataset is from Semeval2018-Task 1 and contains almost 7000 Tweets, labeled with 11 sentiment classes. The second dataset is the Toxic Comment Dataset with more than 150,000 comments, labeled with six different levels of abuse or harassment. Our results suggest that ensemble learning improves classification results by 1.5 % to 5.4 % .

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