• Korean Journal of Child Studies
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• v.25 no.5
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• pp.179-191
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• 2004

An emotion inference task was used to investigate children's cognitive cuing by age, cue type, and situation-emotion fit. Subjects were 41 of 3-, and 5-year-old children from two different day-care centers in Seoul and Kyonggi province. Each child was individually interviewed with pictorial tasks. 5-year-old children demonstrated more cuing, thinking, and application responses than 3-year-old children. Particularly, they showed more situation and thinking responses in situation-emotion match than in situation-emotion mismatch. 3-year-old children showed more past-oriented responses than 5-year-old children. In the interpersonal cue story, there were more situation, past-oriented and thinking responses than in the interobjective ones. The interpersonal cue story produced more situation responses in situation-emotion match than in situation-emotion mismatch.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.7
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• pp.443-450
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• 2013

The high portability and mobility of mobile devices have given rise to critical concerns with regard to mobile situation-aware services that utilize user situation information in the mobile domain. Mobile situation-aware services for mobile devices are provided by collecting and analyzing data, from which the user situation is inferred through an inference system. However, the high mobility of the mobile domain has made it difficult to infer the required results. In addition, previous studies have not identified a systematic approach to modifying and adapting. In this paper, we propose a systematic feedback process model based on software cybernetics in order to address the abovementioned problems. Further, we propose a MADA(Monitoring, Analysis, Determinating, Adaptation) framework for the feedback process model. Thus, the proposed approach supports the development of self-adaptive mobile situation-aware services that can infer appropriate results and manage the inferred results systematically.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.4
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• pp.239-250
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• 2013

Context-aware mobile computing has become the primary approach to realize automatic, autonomous, and user-centric computing in the context of largely increasing the amount of mobile devices used that embed available sensors. However, designing an inference engine nonetheless requires the tasks of analyzing contexts, situations that can be inferred, etc. Moreover, a mobile device has limited resources and limited computation capability, which results in recognizing the common sense of its unsuitable environment for processing inference. Hence, we propose context-situation reasoning elements and their formal models in this paper, and we verify the formal models' applicability by applying them to an example. Finally, we design and implement an inference engine that realize the context-situation inference elements in computing environment, and we experiment an example by using the proposed inference engine to verify applicability and reusability of the inference engine.

• Journal of the Korean Home Economics Association
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• v.43 no.5 s.207
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• pp.221-234
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• 2005

This study investigated the emotional inferences depending on the children's age, character's personality traits, and emotional situations. One hundred three subjects (34 3-year-olds, 33 5-year-olds and 36 7-year-olds) were recruited from 3 daycare centers and 1 elementary school. Eight stories, consisting of four personality traits (positive-'active','helpful', negative-'selfish','mean') and two emotional situations (equivocal and unequivocal situation), were presented with three pictures each. The statistical methods adopted for the data analysis were repeated measure ANOVA, and paired t-test. The results showed that the 3-year-olds showed lower scores of emotional inferences than the 5- and 7-year-olds. However, there were no significant differences between the 5- and 7-year-olds. Children showed more personal inferential responses in the negative personality trait and equivocal situation.

• Child Studies in Asia-Pacific Contexts
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• v.5 no.2
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• pp.83-94
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• 2015

The purpose of this study was to understand the influence of personality trait information on young children's perception of initial attraction in peer relationships. The sample consisted of 90 children of three to five years of age in South Korea. Children were presented with an inductive inference task where they had to make inference of a target character's preference on novel-play and prosocial act based on trait labels (smart-not smart, outgoing-shy, nice-mean) and perceptual (toy) similarity information of two test characters. Children showed difference in their use of trait information depending on the perceptual similarity information, trait valence, and inference question with age. This result provides initial support that not only do young children understand the significance of trait in peer attraction but also know when trait label is more informative to use to infer others depending on the situation.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1079-1085
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• 2014

The analysis of the variable continuous big data stram should reach the destination context awareness. This study presented a novel way of context inference of the variable data stream from sensor motes. For assessment of the sensor data, we calculated the difference of each measured value at the time window and determined the belief value of each focal element. It was beneficial that calculate and assessment of factor of situation for context inference with the Dempster-Shfer evidence theory.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Proceedings of the KSPS conference
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• 2005.11a
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• pp.113-115
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• 2005

In this paper, we present POSSDM (POSTECH Situation-Based Dialogue Manager) for a spoken dialogue system using a new example and situation-based dialogue management techniques for effective generation of appropriate system responses. Spoken dialogue system should generate cooperative responses to smoothly control dialogue flow with the users. We introduce a new dialogue management technique incorporating dialogue examples and situation-based rules for EPG (Electronic Program Guide) domain. For the system response inference, we automatically construct and index a dialogue example database from dialogue corpus, and the best dialogue example is retrieved for a proper system response with the query from a dialogue situation including a current user utterance, dialogue act, and discourse history. When dialogue corpus is not enough to cover the domain, we also apply manually constructed situation-based rules mainly for meta-level dialogue management.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.491-498
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• 1997

This paper describes the arousal measurement and control system using fuzzy logic to prevent drowsy driving. Sugeno's method was used for fuzzy inference in this study. Arousal evaluation and control criteria were modified from result of Nz-IRI analysis depending on arousal sate. Membership function and rule base of fuzzy inference were determined from the modified arousal level criteria When lRl (Inter-SIR Interval) was shorter than 60sec, outputs of both methods were changed from small to big, but output of three step warning method was same level until the next warning range. Since output of fuzzy inference tracked well the change of subject's arousal level, problems of three step warning method could be overcome by fuzzy inference method Furthermore, the output of the fuzzy inference was highly correlated with Nz(r = 0.99). Therefore, the fuzzy inference method for evaluation and the control of arousal will be more effective at real driving situation than three step warning method.

• MALSORI
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• no.56
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• pp.185-194
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• 2005

In this paper, we present POSSDM (POSTECH Situation-Based Dialogue Manager) for a spoken dialogue system using a new example and situation-based dialogue management technique for effective generation of appropriate system responses. Spoken dialogue system should generate cooperative responses to smoothly control dialogue flow with the users. We introduce a new dialogue management technique incorporating dialogue examples and situation-based rules for EPG (Electronic Program Guide) domain. For the system response inference, we automatically construct and index a dialogue example database from dialogue corpus, and the best dialogue example is retrieved for a proper system response with the query from a dialogue situation including a current user utterance, dialogue act, and discourse history. When dialogue corpus is not enough to cover the domain, we also apply manually constructed situation-based rules mainly for meta-level dialogue management.