Breath--Sound of time and space

Thousands of times I have asked myself, why do I draw? Nobody asks me to paint and draw these things, but I am locked in my studio by myself and am drawing each day. Perhaps I draw in order to figure out why I draw. Everyone may have this kind of experience. Since I became a grown-up, I haven\u27t played on a swing which I did quite often during my childhood. A few years ago, I found swings near my house. I tried to swing again but I couldn\u27t do it well. It was hard to recall how to swing. Then one day, I did not worry about how to go high; I just sat down and moved my feet consistently and I started to feel the air and to enjoy that moment. While I was listening to the sound of the birds and trees, I realized that I was so high that I could almost reach the leaves of the big trees surrounding me. I still remember the joy of regaining something that I had forgotten. This is the way I pursue my painting. I always want to feel the creative moment and to be aware of my presence. During that moment, I can remember something that I have forgotten, and I can forget something I have remembered Most of my paintings and drawings are abstract, but also very realistic in the way that I express my emotions. I want my works of art to impact the viewer\u27s inner-self, not merely satisfying with one glance of the eyes but also satisfying the viewer\u27s mind and memory. In this paper, I will present the correlation of image and sound, space and light, and analyze the meaning of lines

A Study on Performance Design Using a Sprinkler System for Fire-Spread Prevention of a Building Exterior

A glass exterior material is normally used in buildings, but it also comes with a disadvantage—it is easily damaged by fire. If the glass exterior material is damaged, a fire can rapidly propagate inside the building space, leading to a lot of damage from the flame transfer to the other space. In this study, the performance of a sprinkler for flame propagation prevention was evaluated during an experiment with an actual proof fire. The study found that where the sprinkler is installed with the glass exterior material, the temperature does not exceed 60°C until the end of the test due to the effect of the water curtain. In the glass exterior material where the sprinkler is not installed, the temperature rapidly increased just after starting the experiment, and caused damage 21 minutes and 30 seconds after starting the test

The Study on Fire Safety by a Real-Scale Combustion Experiment of Composite Material

In this study, a real-scale combustion experiment was carried out for a Styrofoam and glass wool sandwich panel to figure out the fire safety for the composite material used for a building. In the experiment, a heat release rate of a sandwich panel was measured by the ISO 9705 fire test method. Research has also tested and compared temperature change in the Large Scale Calorimeter (LSC) experiment equipment to evaluate the structural safety of the structure body. As a result of the experiment, the structural body with the Styrofoam sandwich panel collapsed which was caused by propagation, and in case of the glass wool sandwich panel, the combustion did no propagate inside. Since the composite material experiences various types of fire hazards depending on the combustion characteristics of the core material, the exact combustion characteristic should be expected by the full-scale combustion experiment

Virtual Reality-Based Psychotherapy in Social Anxiety Disorder: fMRI Study Using a Self-Referential Task

Background: Although it has been well demonstrated that the efficacy of virtual reality therapy for social anxiety disorder is comparable to that of traditional cognitive behavioral therapy, little is known about the effect of virtual reality on pathological self-referential processes in individuals with social anxiety disorder. Objective: We aimed to determine changes in self-referential processing and their neural mechanisms following virtual reality treatment. Methods: We recruited participants with and without a primary diagnosis of social anxiety disorder to undergo clinical assessments (Social Phobia Scale and Post-Event Rumination Scale) and functional magnetic resonance imaging (fMRI) scans. Participants with social anxiety disorder received virtual reality-based exposure treatment for 6 sessions starting immediately after baseline testing. After the sixth session, participants with social anxiety disorder completed follow-up scans during which they were asked to judge whether a series of words (positive, negative, neutral) was relevant to them. Results: Of 25 individuals with social anxiety disorder who participated in the study, 21 completed the sessions and follow-up; 22 control individuals also participated. There were no significant differences in age (P=.36), sex (P=.71), or handedness (P=.51) between the groups. Whole-brain analysis revealed that participants in the social anxiety disorder group had increased neural responses during positive self-referential processing in the medial temporal and frontal cortexes compared with those in the control group. Participants in the social anxiety disorder group also showed increased left insular activation and decreased right middle frontal gyms activation during negative self-referential processing. After undergoing virtual reality based therapy, overall symptoms of the participants with social anxiety disorder were reduced, and these participants exhibited greater activity in a brain regions responsible for self-referential and autobiographical memory processes while viewing positive words during postintervention fMRI scans. Interestingly, the greater the blood oxygen level dependent changes related to positive self-referential processing, the lower the tendency to ruminate on the negative events and the lower the social anxiety following the virtual reality session. Compared with that at baseline, higher activation was also found within broad somatosensory areas in individuals with social anxiety disorder during negative self-referential processing following virtual reality therapy. Conclusions: These fMRI findings might reflect the enhanced physiological and cognitive processing in individuals with social anxiety disorder in response to self-referential information. They also provide neural evidence of the effect of virtual reality exposure therapy on social anxiety and self-derogation

Prediction of Specific Anxiety Symptoms and Virtual Reality Sickness Using In Situ Autonomic Physiological Signals During Virtual Reality Treatment in Patients With Social Anxiety Disorder: Mixed Methods Study

Background: Social anxiety disorder (SAD) is the fear of social situations where a person anticipates being evaluated negatively. Changes in autonomic response patterns are related to the expression of anxiety symptoms. Virtual reality (VR) sickness can inhibit VR experiences. Objective: This study aimed to predict the severity of specific anxiety symptoms and VR sickness in patients with SAD, using machine learning based on in situ autonomic physiological signals (heart rate and galvanic skin response) during VR treatment sessions. Methods: This study included 32 participants with SAD taking part in 6 VR sessions. During each VR session, the heart rate and galvanic skin response of all participants were measured in real time. We assessed specific anxiety symptoms using the Internalized Shame Scale (ISS) and the Post-Event Rumination Scale (PERS), and VR sickness using the Simulator Sickness Questionnaire (SSQ) during 4 VR sessions (#1, #2, #4, and #6). Logistic regression, random forest, and naive Bayes classification classified and predicted the severity groups in the ISS, PERS, and SSQ subdomains based on in situ autonomic physiological signal data. Results: The severity of SAD was predicted with 3 machine learning models. According to the F1 score, the highest prediction performance among each domain for severity was determined. The F1 score of the ISS mistake anxiety subdomain was 0.8421 using the logistic regression model, that of the PERS positive subdomain was 0.7619 using the naive Bayes classifier, and that of total VR sickness was 0.7059 using the random forest model. Conclusions: This study could predict specific anxiety symptoms and VR sickness during VR intervention by autonomic physiological signals alone in real time. Machine learning models can predict the severe and nonsevere psychological states of individuals based on in situ physiological signal data during VR interventions for real-time interactive services. These models can support the diagnosis of specific anxiety symptoms and VR sickness with minimal participant bias

Prediction of Specific Anxiety Symptoms and Virtual Reality Sickness Using In Situ Autonomic Physiological Signals During Virtual Reality Treatment in Patients With Social Anxiety Disorder: Mixed Methods Study

Background: Social anxiety disorder (SAD) is the fear of social situations where a person anticipates being evaluated negatively. Changes in autonomic response patterns are related to the expression of anxiety symptoms. Virtual reality (VR) sickness can inhibit VR experiences. Objective: This study aimed to predict the severity of specific anxiety symptoms and VR sickness in patients with SAD, using machine learning based on in situ autonomic physiological signals (heart rate and galvanic skin response) during VR treatment sessions. Methods: This study included 32 participants with SAD taking part in 6 VR sessions. During each VR session, the heart rate and galvanic skin response of all participants were measured in real time. We assessed specific anxiety symptoms using the Internalized Shame Scale (ISS) and the Post-Event Rumination Scale (PERS), and VR sickness using the Simulator Sickness Questionnaire (SSQ) during 4 VR sessions (#1, #2, #4, and #6). Logistic regression, random forest, and naïve Bayes classification classified and predicted the severity groups in the ISS, PERS, and SSQ subdomains based on in situ autonomic physiological signal data. Results: The severity of SAD was predicted with 3 machine learning models. According to the F1 score, the highest prediction performance among each domain for severity was determined. The F1 score of the ISS mistake anxiety subdomain was 0.8421 using the logistic regression model, that of the PERS positive subdomain was 0.7619 using the naïve Bayes classifier, and that of total VR sickness was 0.7059 using the random forest model. Conclusions: This study could predict specific anxiety symptoms and VR sickness during VR intervention by autonomic physiological signals alone in real time. Machine learning models can predict the severe and nonsevere psychological states of individuals based on in situ physiological signal data during VR interventions for real-time interactive services. These models can support the diagnosis of specific anxiety symptoms and VR sickness with minimal participant bias.11Ysciescopu

Job Analysis of Korean Occupational Therapists based on the DACUM method

Objective : The purposes of this study were to analyze the duties of occupational therapists through the DACUM method, and to present the importance and frequency of the main duties and tasks currently conducted in Korea. Methods : The DACUM method was used to achieve an analysis of the duties of Korean occupational therapists in the present day. In order to achieve this analysis, a DACUM committee was created, a job analysis was executed through a DACUM workshop, and a survey was conducted on 252 Korean occupational therapists working in metropolitan areas in order to analyze the order of priority for all tasks. Results : This study defined the task of occupational therapists and presented 4 duties (assessment,treatment, education, administration and management) and 21 tasks. Important items in each duty among all tasks were decided by conducting a survey in the job analysis committee, which included presenting an interpretation of the results of a duty assessment, execution of treatment, patient and guardian education, and document administration and management, thus coinciding with the order of priority in all duties excluding education. However, the importance of tasks presented a difference according to job factors, such as rank,career, and work classification. Conclusions : The results of this study will be of help for the development of a university curriculum and an improvement in the continuing education content of special interest sections

A Study of the Effectiveness Verification of Computer-Based Dementia Assessment Contents (Co-Wis): Non-Randomized Study

Computer-based neuropsychological assessments have many advantages over traditional neuropsychological assessments. However, limited data are available on the validity and reliability of computer-based assessments. The purpose of this study was to examine the reliability and validity of computer-based dementia assessment contents (Co-Wis). This study recruited 113 participants from Yeungnam University Medical Center in Daegu from June 2019 to December 2019 and received ethical approval. Participants were evaluated using standard and objective dementia cognitive test tools such as the Korean version of the Mini-Mental State Examination (K-MMSE), the Clinical Dementia Rating Scale (CDR), and the Standardized Seoul Neuropsychological Screening Battery-II (SNSB-II). To verify the effectiveness of Co-Wis, the concurrent validity, test–retest reliability (Pearson’s correlation coefficients), construct validity (Factor analysis), and signal detection analysis (ROC curve) were used. In most of the Co-Wis subtests, the concurrent validity and test–retest reliability showed statistically significant correlations (p < 0.05, p < 0.01). The factor analysis showed that Co-Wis assessed the most major cognitive areas (Tucker–Lewis Index (TLI) = 0.876, Comparative Fit Index (CFI) = 0.897, RMSEA = 0.88). Thus, Co-Wis appears clinically applicable and with high reliability and validity. In the future, we should develop tests to evaluate both standard data and big data-based machine learning

Visuo-Haptic-Based Multimodal Feedback Virtual Reality Solution to Improve Anxiety Symptoms: A Proof-of-Concept Study

With proper guidance, virtual reality (VR) can provide psychiatric therapeutic strategies within a simulated environment. The visuo-haptic-based multimodal feedback VR solution has been developed to improve anxiety symptoms through immersive experience and feedback A proof-of-concept study was performed to investigate this VR solution. Nine subjects recently diagnosed with panic disorder were recruited, and seven of them eventually completed the trial. Two VR sessions were provided to each subject. Depression, anxiety, and VR sickness were evaluated before and after each session. Although there was no significant effect of the VR sessions on psychiatric symptoms, we could observe a trend of improvement in depression, anxiety, and VR sickness. The VR solution was effective in relieving subjective anxiety, especially in panic disorder without comorbidity. VR sickness decreased over time. This study is a new proof-of-concept trial to evaluate the therapeutic effect of VR solutions on anxiety symptoms using visuo- hartic-based multimodal feedback simultaneously