• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.1
• /
• pp.113-117
• /
• 2018

Human emotions are revealed by various factors. Words, actions, facial expressions, attire and so on. But people know how to hide their feelings. So we can not easily guess its sensitivity using one factor. We decided to pay attention to behaviors and facial expressions in order to solve these problems. Behavior and facial expression can not be easily concealed without constant effort and training. In this paper, we propose an algorithm to estimate human emotion through combination of two results by gradually learning human behavior and facial expression with little data through the deep learning method. Through this algorithm, we can more comprehensively grasp human emotions.

• Korean Journal of Psychosomatic Medicine
• /
• v.24 no.1
• /
• pp.54-60
• /
• 2016

Alexithymia is characterized by difficulties identifying and describing feelings, impoverished fantasy life, and concrete and poorly introspective thinking. Alexithymic patients have been reported to show a stable deficit with regard to processing and regulating emotions. Eating disorders are characterized by a persistent disturbance of eating or eating-related behavior that significantly impairs physical health or psychosocial functioning. Like alexithymic patients, patients with eating disorders show the impaired capacity to process and regulate emotions. There is a robust body of literature showing patients with eating disorders are more alexithymic than healthy controls. Specifically, patients with eating disorders experience difficulties identifying and describing emotions. Childhood maltreatment can increase the risk for depression and alexithymia, which can in turn lead to disordered eating symptoms. Also, higher levels of alexithymia are correlated with a less favorable clinical outcome in patients with eating disorder. Therefore, treatments to help processing and regulating emotions of eating disorder patients with pronounced alexithymic traits may seem to lead to a higher possibility of recovery.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.7 no.2
• /
• pp.258-266
• /
• 1996

Self-injurious behaviors are commoly founded in the case of the developmentally impaired, such as mental retardation and autistic disorder. These behaviors are primary serious sources of distress for both child and their parents, another obstacle to overcome within the family and society. The author has a case that a child, had never before shown self-injurious behaviors. He abruptly started to injury his face and heel. The beginnings of these harmful behaviors are associated with symptoms of physical illness, such as fever, chills and general aches. The self-injured wounds were very severe. After the patient was treated with haloperidol and improved his physical conditions, self-injurious behaviors disappeared. The author reports the child's clinical process, characteristics of self-injurious behaviors, and discuss the treatment factors, along with a literature review.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.6
• /
• pp.627-633
• /
• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• Journal of Korean Society of Transportation
• /
• v.21 no.3
• /
• pp.97-106
• /
• 2003

When a route choice is done under uncertainty, a driver has some expectation of traffic conditions that will occur according to the route chosen. This study tries to build a framework in which we can observe the learning behavior of the drivers' expectations of the travel time under nonstationary environment. In order to investigate how drivers have their subjective expectations on traffic conditions in response to public information, a numerical experiment is carried out. We found that rational expectations(RE) formation about the route travel time can be expressed by the adaptive expectation model when the travel time changes in accordance with the nonstationary process which consists of permanent shock and transient shock. Also, we found that the adaptive parameter of the model converges to the fixed value corresponding to the route conditions.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
• /
• v.14 no.2
• /
• pp.218-228
• /
• 2003

Objectives：This study investigated the relationship among child's behavior problems, maternal depression, and parenting stress in children with psychiatric diagnoses and their mothers, and the effect of these variables to the mothers' parenting stress. Methods：Seventy-three children(31 externalizing, 24 internalizing, 18 mixed) and their mothers were involved in this study. The mothers of three groups completed MMPI, KPI-C(Korean Personality Inventory for Children), and PSI(Parenting Stress Index). To investigate the relationships among each variables, ANOVA, Pearson correlation, stepwise regression analysis were performed. Results：There was no significant difference in maternal depression among three groups of children. In 2-Way ANOVA, main effect of maternal depression was statistically significant on depression, parent health, and relationship with spouse subfactor in parent domain, parent domain total, and overall parenting stress. But the main effect of child group was statistically significant on distractability/hyperactivity subfactor in child domain only. In regression analysis, maternal depression explained the parent domain of parenting stress most effectively, and child's hyperactivity and anxiety explained the child domain of parenting stress significantly. Conclusion：These findings suggest that it is important to intervene maternal depression to reduce the parenting stress, along with the treatment of the child's behavior problems.

• Industry Promotion Research
• /
• v.9 no.3
• /
• pp.229-240
• /
• 2024

The purpose of this study was to develop a program to prevent recurrence, focusing on cognitive and behavioral factors to reduce gambling game behavior in children, and to verify the effectiveness to analyze basic data necessary for prevention education. Eight children in the 4th to 6th grades of male students were selected, an experiment and control group were formed, and the effectiveness was verified only after 3 months after the experimental group was conducted once a week. First, irrational gambling beliefs, the level of gambling problems, automatic thinking for children, and the level of gambling problems were reduced through cognitive behavior therapy programs to reduce gambling game behavior in children. Changes in maladaptive thinking that directly affect gambling game behavior instilled awareness of gambling game behavior. Second, self-control and impulsiveness, the behavioral variables, did not show any significant difference, but decreased in the overall average. Changes in cognitive variables influenced behavioral variables. Third, it was found to continue even 3 months after the end of the program. Changes in cognitive and behavioral variables later reduced children's gambling game behavior and helped school life and peer relationships through adaptive thinking.

• Journal of KIISE:Software and Applications
• /
• v.41 no.7
• /
• pp.457-468
• /
• 2014

Recently, several approaches are proposed to support developing Self-Adaptive System. However, they do not provide the way to accept interaction between requirements and architecture. It makes difficult to judge the impact of changing requirements, handle quickly, and understand adaptation process for stakeholder. To overcome above problems, this paper suggests the interweaving method for providing traceability based on the relationship between requirements and architecture. This traceability allows tracing the impact of changing requirements, and it provides the rationale of architectural decision for advanced degree of understanding. Example shows the usefulness through developing process and changing process on Smart Grid domain.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.2
• /
• pp.429-440
• /
• 2015

This study was to investigate factors influencing the school adjustment according to gender and body mass index (BMI) of middle school students who participated in the 2nd-wave Korea Children and Youth Panel Study (KCYPS). This study used a crosssectional design with secondary analysis with KCYPS. The variables were parental interest, behavioral problem, aggression, attention problem, somatic symptom, social withdrawal, depression, and academic achievement. The data were analyzed with descriptive statistics, Pearson's correlation coefficients, and multiple regressions. School adjustment was significantly associated with academic achievement high, explaining 11.3~19.1% of the variance in boys. School adjustment was significantly associated with attention problem, explaining 14.9~42.4% of the variance in girls. Factors influencing school adjustment were significantly different according to gender and BMI. To improve the school adjustment, it is necessary to develop gender-specific school adjustment promotion programs according to BMI.

• Journal of KIISE
• /
• v.43 no.7
• /
• pp.801-811
• /
• 2016

Self-adaptive systems (SASs) can change their goals and behaviors to achieve its ultimate goal in a dynamic execution environment. Existing approaches have designed, at the design time, utility functions to evaluate and predict the goal satisfaction, and set policies that are crucial to achieve each goal. The systems can be adapted to various runtime environments by utilizing the pre-defined utility functions and policies. These approaches, however, may or may not guarantee the proper adaptability, because system designers cannot assume and predict all system environment perfectly at the design time. To cope with this problem, this paper proposes a new method of dynamic decision making, which takes the following steps: firstly we design a Dynamic Decision Network (DDN) with environmental data and goal model that reflect system contexts; secondly, the goal satisfaction is evaluated and predicted with the designed DDN and real-time environmental information. We furthermore propose a dynamic reflection method that changes the model by using newly generated data in real-time. The proposed method was actually applied to ROBOCODE, and verified its effectiveness by comparing to conventional static decision making.