Minetada Osano

Towards recognizing emotion with affective dimensions through body gestures

Due to the ever-increasing importance of computers in many areas of todays society such as e-learning, telehome-health care, and entertainment, their ability to interact well with humans is essential. Currently, researchers are using facial expression and voice recognition modalities to create systems that interact with humans. But still two problems exist: gesture is not yet a concern as a channel of affective communication in interactive technology, and existing systems only model discrete categories but not affective dimensions, e.g., intensity. Our focus has been on creating affective gesture recognition system that recognize childs emotion with intensity through body gestures in context of game. This information is then used by a game control module that users a rule-based adaptation model to change game level according to the childs intensity of emotions. Results show that affective gesture recognition model recognized childs emotion over 79% of the cases and the proposed intensity estimate model has a strong relationship with observer perception except in the low intensity level

A Computational Model for Recognizing Emotion with Intensity for Machine Vision Applications

One of the challenging issues in affective computing is to give a machine the ability to recognize the affective states with intensity of a person. Few studies are directed toward this goal by categorizing affective behavior of the person into a set of discrete categories. But still two problems exist: gesture is not yet a concern as a channel of affective communication in interactive technology, and existing systems only model discrete categories but not affective dimensions, e.g., intensity. Modeling the intensity of emotion has been well addressed in synthetic autonomous agent and virtual environment literature, but there is an evident lack of attention in other important research areas such as affective computing, machine vision, and robotic. In this work, we propose an affective gesture recognition system that can recognize the emotion of a child and the intensity of the emotion states in a scenario of game playing. We used levels of cognitive and non-cognitive appraisal factors to estimate intensity of emotion. System has an intelligent agent (called Mix) that takes these factors into consideration and adapt the game state to create a more positive interactive environment for the child.

A model for negotiation among agents based on the transaction analysis theory

In the research work presented, interactions among the various types of agents in autonomous decentralized systems are based on the theory of transaction analysis (TA) of psychology. Human beings are considered one particular type of autonomous agent. Hence, the agents structure as well as interactions among them are defined and performed much the same as human behavior and attitudes. Cooperation among agents is negotiated by exchanging strokes. After the cooperation among agents is established, each of them has a specific role to perform in order to reach a particular goal. The paper presents the definition of the inner structure of an agent along with the negotiation process occurred among them until the cooperation is established.<<ETX>>

A Multi-agent Based Interactive System Towards Child&#146;s Emotion Performances Quantified Through Affective Body Gestures

Studies in cognitive science have found that interactive robots, interactive games, etc., may help the emotional development of children with mental-health problems (e.g. autistic children). It is very important with these children to show empathic behaviors and to take into account their emotion when relating to them. Current technology cannot do this because it cannot recognize the emotion of the children. Few studies are directed toward this goal by categorizing affective behavior of the child into a set of discrete categories. But still two problems exist: gesture is not yet a concern as channel of affective communication in interactive technology, and existing systems only model discrete categories, but not affective dimensions, e.g., intensity. In this work, we propose a multi-agent based interactive system that can quantify childsperformance (emotion with intensity of emotion) in real time

A new efficient solution method for a system of linear equations: Partially Solving Method (PSM)

We present a new method of solving a system of linear equations, called Partially Solving Method (PSM). The PSM can essentially deal with only a subsystem at each processing stage without complete knowledge of the entire system. For dense systems, it reduces the necessary memory space effectively by a factor of four as compared with the conventional LU-decomposition method. For sparse systems, the method operates up to, twice as fast as Gaussian elimination method, and the efficiency in both space and time is further enhanced by a proper ordering of selections of the equations. It may be feasible to apply the PSM in a parallel processing environment, when the entire system is divided into subsystems.

An Interactive E-learning System Using Kansei Engineering

An important issue faced today in any on-line system is to determine the users’ states of emotions regarding the situation. It is possible to identify user’s emotions while interacting face to face by observing their conditions, and assign a suitable level of tasks to the user. But it is very much difficult to identify the user’s state of emotion when he or she is not in front of teacher when communicating is in progress. Kansei Engineering is used in this research, to achieve a solution to this problem. Learner’s knowledge level of the lesson and emotional level are considered as key parameters to measure the status of the learner. These measurements are used as key points to enhance the experience of the learner, who is interacting with the E-Learning system. The E-Learning system supports in customized ways to the learner, to improve knowledge and manage emotions effectively.

Monitoring of emotion to create adaptive game for children with mild autistic

Computer-based interactive systems and robots have become a massive technology for improving human-impaired social interaction, especially for children with autistic. Autism is a lifelong development disability, often accompanied by learning technologies. As a result, they have trouble interacting within our complex social environment and are, for the most part, unable to recognize other peoples behaviors. In this paper, we present game-based therapeutic environments for people diagnosed with a mild form of autism. The proposed interactive system traces a childs emotion with intensity for changing a game environment for the purpose of triggering their emotions. The pedagogical agent provides therapy instruction with motivational support to children through adapting a childs emotional behaviors.

Therapeutic Tool for Develop Child Nonverbal Communication Skills through Interactive Game

In this paper, an interactive multi-agent based system that recognizes childs emotions and the intensity of emotions to build systems for therapeutic purposes (developed childs non-verbal communication skills) is presented. It introduces the development of an arousal perception agent that uses a novel emotion intensity estimation model. The arousal perception agent uses cognitive and non-cognitive factors to estimate a childs intensity of emotions in real time. Flexible and a novel adaptation model based on emotional intensity is developed for the proposed situational control agent. The situational control agent tries to adjust the intensity of negative and positive emotions by changing the status of the game to encourage children to express natural emotions. This situational control agent reacts as therapy (adjusting motivational and encouragement support) for developing childrens emotional expression through affective body gestures. An animated pedagogical agent gives motivational help with instructions (like therapy) as a means of encouragement to naturally express emotions by adapting the system in an interactive manner.

A distributed method for solving nonlinear equations applying the power load flow calculation

A new approach for distributed power load flow calculation using nonlinear equations is presented. This approach, which is similar to the Newton Raphsons simple method, uses an inverse Jacobian matrix of initial states for the iteration process. Moreover, nonlinear quadratic equations have been used as they are more appropriate for the distributed power load flow calculation. The paper describes and compares the new approach with the Newton Raphson method. It shows that such an approach is more suitable for distributed power load flow calculation as well as discussing some of its applications.

A decentralized social algorithm for committee coordination problem

We consider an extended committee coordination problem in an autonomous decentralized social environment. The basic committee coordination problem and a distributed algorithm, as a solution to this problem in a distributed environment, are presented by K.M. Chandy and J. Misra (1988). The algorithm guarantees the synchronous and exclusion properties of the problem and is fair (i.e. starvation-free) and makes progress (i.e. deadlock-free). In an autonomous decentralized social environment, besides the above mentioned properties, some social properties, such as individual preference, privacy protection, and stable assignment, are required to be considered and guaranteed. We extend the committee coordination problem by introducing some social properties, such as individual preference and stable assignment and give a decentralized social algorithm as a solution to this extended problem. The algorithm guarantees not only the synchronous and exclusion properties but also individual preference and stable assignment properties.<<ETX>>