• Journal of Korean Society of Disaster and Security
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• v.9 no.2
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• pp.53-62
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• 2016

This paper is shown the new method using LED Light, which the light environment is upgraded the natural LED light in the area of Disaster Prevention and Safety Management (PDSD), which the events of deaths is reduced on the Suicide, the Infectious diseases, the safety accidents, the Traffic Accident, the crime, the fire, the Nature Disaster, and which the health and the environment and the safety is implemented using the value of the color LED Light. Research findings include,during 3 weeks in the November 2016, in the ten residents (average living 28.7 years, age 67.5 years) with depressive symptoms in the northern part of Seoul, according to the request of the user, the PDSD natural light LED lighting was installed in the home bedroom or the living room, expectations for the ability to restore physical and mental stability were high (88%), in the same way, after 1 week and 3 weeks, the physical and mental changes were compared and the results,84% in the first week and 90% in the third week and thereafter, the effect of relieving depression was high. We conclude that patients with depression have a good sleep, an uneasy feeling, a sense of security, a good night's sleep, and a good feeling. The PDSD LED Light is expected to contribute in the various areas, which reduced the suicides, which give increased immunity from infectious diseases, which give a crash to reduce accidents caused by negligence, which improve the safe operation of heavy vehicles in which a traffics accident incidence installed on the highest point, which improve the safety function on the 'safety way home' for the safety of the community, which due to fire gives alleviate the emotional anxiety of firefighters, which improve the environment for long-term control room working during decision making caused by natural disasters.

• The Journal of Korean Academy of Sensory Integration
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• v.9 no.2
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• pp.51-60
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• 2011

Objective : The characteristics of physiological responses of ADHD children to sensory stimulation were examined by types of sensory stimulation, measurement tools, and responses. In addition the behavioral characteristics were examined by analyzing items of common problems according to the measuring tool, frequency, and measurement tools. Methods : A systematic review methods were used. Papers published in the Journal between January, 1990 and December 31, 2011 were searched through Riss4U, MEDLINE /PubMed, CINAH. The main terms searched were "ADHD, Children, Sensory processing, Sensory integration, SP, SSP, SOR, TIE, CSP, SEP, EDR", and 15 papers were analyzed. Results : 1. The number of studies on physiological responses of children with ADHD to sensory stimulation was five (33.33 percent), the number of studies on behavioral responses was ten(66.67%), and the number of studies combined the two kinds of study was two (13.33%), where a total of 15 (100%) papers were analyzed. 2. In five studies on the physiological response, there were three studies using tactile and proprioceptive stimulations and two studies using olfactory, auditory, visual, tactile, and vestibular sensories. 3. In ten studies on the behavioral responses, there were five studies using SP, three studies using SSP, two studies using SOR, one study using TIE, and one study using CSP. Conclusion : In the characteristics of physiological responses of children with ADHD children to sensory stimulation, there was in the action potential of the cells in hand region of the primary sensorimotor cortex neurons. It was analyzed that there was an initial state and it appeared show a obvious and fast habituation in the later state; the time of recovery seemed to have many non-specific responses. In the characteristics of behavioral responses, there were inattention / distraction, vestibular processing, sensory processing related to endurance / tone, modulation of sensory input affecting emotional responses, low energy/weak.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.877-895
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• 2014

It is common sense that providing specific odor can increase the video reality when video scene has an object having specific odor. However, people still do not know how to increase video reality and emotional immersion when there is no information on specific odor in the scene. So, present study explores how we improve video reality and immersion when the scene has no concrete odor information from some objects. Especially, this research focuses on diverse previous studies about matching between odor and color and then we expect providing odor can increase video reality if the odor is well-matched with the video's color. To do this, we collected 48 odors and investigated which color was well-matched with each odor. As a result, we get 5 odors which had clearly well-matched colors and decide ill-matched colors of those 5 odors as complementary colors of well-matched colors (Experiment 1). After that, we organize 3 conditions such as coloring image and video clip with well-matched color (color-odor match condition), coloring those with ill-matched color (color-odor mismatch condition), and coloring those with achromatic color by removing color saturation (color-odor neutral condition). Under each of these three conditions, image-odor matching, increment of reality with the odor, increment of immersion with the odor, and odor preference are asked (Experiment 2; 3). The results showed that the scores of all 4 questions in color-odor match condition were higher than color-odor mismatch condition and neutral condition. These results mean that providing matching odor with the scene's color in video is very effective to increase video reality and immersion. We expect experiencing better reality and immersion with olfactory information by adding various future research.

• Journal of Home Health Care Nursing
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• v.4
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• pp.5-22
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• 1997

The purpose of the study was to development an information delivery system for the home nursing service, to demonstrate and to evaluate the efficiency of it. The period of research conduct was from September 1996 to August 31, 1997. At the 1st stage to achieve the purpose, Firstly Assessment tool for the patients with cerebral vascular disease who have the first priority of HNS among the patients with various health problems at home was developed through literature review. Secondly, after identification of patient nursing problem by the home care nurse with the assessment tool, the patient's classification system developed by Park (1988) that was 128 nursing activities under 6 categories was used to identify the home care nurse's activities of the patient with CAV at home. The research team had several workshops with 5 clinical nurse experts to refine it. At last 110 nursing activities under 11 categories for the patients with CVA were derived. At the second stage, algorithms were developed to connect 110 nursing activities with the patient nursing problems identified by assessment tool. The computerizing process of the algorithms is as follows: These algorithms are realized with the computer program by use of the software engineering technique. The development is made by the prototyping method, which is the requirement analysis of the software specifications. The basic features of the usability, compatibility, adaptability and maintainability are taken into consideration. Particular emphasis is given to the efficient construction of the database. To enhance the database efficiency and to establish the structural cohesion, the data field is categorized with the weight of relevance to the particular disease. This approach permits the easy adaptability when numerous diseases are applied in the future. In paralleled with this, the expandability and maintainability is stressed through out the program development, which leads to the modular concept. However since the disease to be applied is increased in number as the project progress and since they are interrelated and coupled each other, the expand ability as well as maintainability should be considered with a big priority. Furthermore, since the system is to be synthesized with other medical systems in the future, these properties are very important. The prototype developed in this project is to be evaluated through the stage of system testing. There are various evaluation metrics such as cohesion, coupling and adaptability so on. But unfortunately, direct measurement of these metrics are very difficult, and accordingly, analytical and quantitative evaluations are almost impossible. Therefore, instead of the analytical evaluation, the experimental evaluation is to be applied through the test run by various users. This system testing will provide the viewpoint analysis of the user's level, and the detail and additional requirement specifications arising from user's real situation will be feedback into the system modeling. Also. the degree of freedom of the input and output will be improved, and the hardware limitation will be investigated. Upon the refining, the prototype system will be used as a design template. and will be used to develop the more extensive system. In detail. the relevant modules will be developed for the various diseases, and the module will be integrated by the macroscopic design process focusing on the inter modularity, generality of the database. and compatibility with other systems. The Home care Evaluation System is comprised of three main modules of : (1) General information on a patient, (2) General health status of a patient, and (3) Cerebrovascular disease patient. The general health status module has five sub modules of physical measurement, vitality, nursing, pharmaceutical description and emotional/cognition ability. The CVA patient module is divided into ten sub modules such as subjective sense, consciousness, memory and language pattern so on. The typical sub modules are described in appendix 3.

• Journal of the Korean Institute of Landscape Architecture
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• v.45 no.2
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• pp.76-88
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• 2017

The urban park plays important roles in protecting the urban landscape and improving citizens' health, recreation, and the emotional life. Above and beyond these roles, the urban park is expected to rearrange urban spatial structures as a kind of urban system. The purpose of this paper is to identify empirically to change urban spatial structures by construction of the urban park. This study regards gentrification around the urban park as a process to change urban spatial structures. The gentrification means the regeneration and upgrading of deteriorated urban property by the middle class or commercial developers. The site of case analysis is the Seoul Forestry Park in Sungdong-gu, Seoul. The Seoul Forestry Park is regarded as a representative urban park of Seoul, and caused gentrification around park after the 2005 opening. This study operationally defines the gentrification index and the accessibility index from an urban park and offers an empirical analysis of relation among the urban park, the gentrification and urban spatial structure in a statistic district which is the minimum unit of Korean statistic data in 2000, 2005, and 2010, using Difference-in-Difference method and linear probability model. The results of this empirical study show that the Seoul Forestry Park changes urban spatial structures by gentrification. It reverses a trend of migration of gentrifiers before and after construction of the Seoul Forestry Park. It suggests urban park construction as an alternative method for urban regeneration by inducing the middle class into the inner city of Seoul.

• Journal of the Korean Applied Science and Technology
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• v.37 no.6
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• pp.1517-1527
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• 2020

This study is about the UV protection effect and water resistance of a multiple emulsion (W/O/W) sunblock cream applied with emotional engineering and reports an actual industrial case. Multiple emulsion system of sunblock cream has the characteristics of changing to a W/O type that is soft and moist when applied, and has excellent water resistance after absorption. Multiple emulsion cream is a highly functional sunblock cream that has both moisture and water resistance. It is a stable milky white cream with a viscosity of 36,000 cps. The organic sunscreen used for the sunscreen was ethylhexylmethoxycinnamate and bisethylhexyloxyphenolmethoxyphenyltriazine. Hexagonal zinc oxide and titanium dioxide that block both UVB and UVA were used. As a result of measuring the UV protection effect by the in-vitro method, the UV protection effect (SPF) is 78.9 for multiple emulsion cream, 76.7 for W/O cream, and 71.3 for O/W cream. It was found that the blocking effect was different. This obtained the highest effect value in the multiple emulsion. As a clinical (in-vivo) result of the UV protection effect, the SPF value representing the UV protection effect of the sunblock cream developed with a multiple emulsion system was 85.7, and the PA-value that blocks the UVA area was 26.5, and ++++. It was found that it has a corresponding high blocking effect. As a result of the water resistance test, the W/O/W formulation had a high waterproofing resistance of 93.8% even after 4 hours, W/O had 75.4%, and O/W had a low water resistance of 25.3%. In the results of the HUT test, it was found in the order of multiple emulsion sun block cream > hydrophilic cream > lipophilic cream. Based on the research results of this multiple emulsion, it is expected to be highly active as a sunblock cream dedicated to outdoor activities by improving the feeling of use, UV protection index, and water resistance. Therefore, in this study, a multiple emulsion system of sunblock cream is developed and has a characteristic that changes to a W/O type that has a soft and moist feeling when applied, and has excellent water resistance after absorption.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.139-156
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• 2021

The biggest reason for using a deep learning model in image classification is that it is possible to consider the relationship between each region by extracting each region's features from the overall information of the image. However, the CNN model may not be suitable for emotional image data without the image's regional features. To solve the difficulty of classifying emotion images, many researchers each year propose a CNN-based architecture suitable for emotion images. Studies on the relationship between color and human emotion were also conducted, and results were derived that different emotions are induced according to color. In studies using deep learning, there have been studies that apply color information to image subtraction classification. The case where the image's color information is additionally used than the case where the classification model is trained with only the image improves the accuracy of classifying image emotions. This study proposes two ways to increase the accuracy by incorporating the result value after the model classifies an image's emotion. Both methods improve accuracy by modifying the result value based on statistics using the color of the picture. When performing the test by finding the two-color combinations most distributed for all training data, the two-color combinations most distributed for each test data image were found. The result values were corrected according to the color combination distribution. This method weights the result value obtained after the model classifies an image's emotion by creating an expression based on the log function and the exponential function. Emotion6, classified into six emotions, and Artphoto classified into eight categories were used for the image data. Densenet169, Mnasnet, Resnet101, Resnet152, and Vgg19 architectures were used for the CNN model, and the performance evaluation was compared before and after applying the two-stage learning to the CNN model. Inspired by color psychology, which deals with the relationship between colors and emotions, when creating a model that classifies an image's sentiment, we studied how to improve accuracy by modifying the result values based on color. Sixteen colors were used: red, orange, yellow, green, blue, indigo, purple, turquoise, pink, magenta, brown, gray, silver, gold, white, and black. It has meaning. Using Scikit-learn's Clustering, the seven colors that are primarily distributed in the image are checked. Then, the RGB coordinate values of the colors from the image are compared with the RGB coordinate values of the 16 colors presented in the above data. That is, it was converted to the closest color. Suppose three or more color combinations are selected. In that case, too many color combinations occur, resulting in a problem in which the distribution is scattered, so a situation fewer influences the result value. Therefore, to solve this problem, two-color combinations were found and weighted to the model. Before training, the most distributed color combinations were found for all training data images. The distribution of color combinations for each class was stored in a Python dictionary format to be used during testing. During the test, the two-color combinations that are most distributed for each test data image are found. After that, we checked how the color combinations were distributed in the training data and corrected the result. We devised several equations to weight the result value from the model based on the extracted color as described above. The data set was randomly divided by 80:20, and the model was verified using 20% of the data as a test set. After splitting the remaining 80% of the data into five divisions to perform 5-fold cross-validation, the model was trained five times using different verification datasets. Finally, the performance was checked using the test dataset that was previously separated. Adam was used as the activation function, and the learning rate was set to 0.01. The training was performed as much as 20 epochs, and if the validation loss value did not decrease during five epochs of learning, the experiment was stopped. Early tapping was set to load the model with the best validation loss value. The classification accuracy was better when the extracted information using color properties was used together than the case using only the CNN architecture.