• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2687-2692
• /
• 2003

Recent advancement in information technology requires new interpretations for the space among human, machines and environment. Investigation of space between information and human could lead to the proper ways, in which human and machines meet. Various concepts regarding space have been explored in terms of “virtual reality in cyberspace” and “embodiment in tangible space.” “Mom (embodiment),” space, virtuality, sensation/perception, and interactive technology are some of the key ideas to be explored. Human “Mom” is such a fundamental membrane through which human can interact with the environment physically and mentally. An embodied interaction paradigm, based on “Mom,” is investigated. This leads to interactive technology paradigm. Sound space is an invisible but a tangible space in a sense that it travels in emotional tremors and stimulates new sensations and perceptions. Three cases are introduced to experiment such tangible space as a new and proper interactive paradigm. Also, a historical model of interaction is reviewed, which includes electrical, symbolic, textual, graphical, tangible, and social interaction.

• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.8
• /
• pp.393-400
• /
• 2016

Recently, there have been various researches on efficient and automatic analysis on urban environment methods that utilize the computer vision and machine learning technology. Among many new analyses, urban safety analysis has received a major attention. In order to predict more accurately on safety score and reflect the human visual perception, it is necessary to consider the generic and local information that are most important to human perception. In this paper, we use Double-column Convolutional Neural network consisting of generic and local columns for the prediction of urban safety. The input of generic and local column used re-sized and random cropped images from original images, respectively. In addition, a new learning method is proposed to solve the problem of over-fitting in a particular column in the learning process. For the performance comparison of our Double-column Convolutional Neural Network, we compare two Support Vector Regression and three Convolutional Neural Network models using Root Mean Square Error and correlation analysis. Our experimental results demonstrate that our Double-column Convolutional Neural Network model show the best performance with Root Mean Square Error of 0.7432 and Pearson/Spearman correlation coefficient of 0.853/0.840.

• Journal of Environmental Health Sciences
• /
• v.43 no.5
• /
• pp.360-369
• /
• 2017

Objectives: The organizational culture of small-scale enterprises is influenced by a lack of awareness of industrial accidents and a business-oriented culture. Therefore, the purpose of this study is to establish a correlation between chemical awareness and worker safety, which is the reason why a company's safety environment is responsible for human factor accidents. Methods: The research model established the organizational culture, human relationships, organizational relationships, workplace culture, safety climate, and safety parameters, all of which affect the perception of chemical substances, then established safety rankings, communication, safety regulations, and safety support. Results: In order to derive the results of this study, the satisfaction level was mostly derived from the degree of engagement (+) depending on the number of years worked, in the hierarchical regression analysis. During work with chemicals, the number of years spent on the level of the service was determined by the influence of the chemical (-). Based on this company, the occurrence of chemical accidents caused by chemical materials was felt to be felt at the risk of causing the hazard to be felt, the absence of physical damage was excluded from the variables. The other variables detected in the variables were $62.8{\pm}24.4$. Conclusion: As a result, it is necessary to develop a statistical model for the verification of the hierarchical regression analysis, and the relationship between safety and awareness of the dangers of chemicals and biological agents requires periodic safety training. Job satisfaction was found to be higher if the level of awareness was sufficient.

• Journal of Internet of Things and Convergence
• /
• v.10 no.2
• /
• pp.51-60
• /
• 2024

Aiming at the problem of low contrast and difficult to recognize video images in low-light environment, we propose an adaptive contrast compensation enhancement algorithm based on human visual perception. First of all, the video image characteristic factors in low-light environment are extracted: AL (average luminance), ABWF (average bandwidth factor), and the mathematical model of human visual CRC(contrast resolution compensation) is established according to the difference of the original image's grayscale/chromaticity level, and the proportion of the three primary colors of the true color is compensated by the integral, respectively. Then, when the degree of compensation is lower than the bright vision precisely distinguishable difference, the compensation threshold is set to linearly compensate the bright vision to the full bandwidth. Finally, the automatic optimization model of the compensation ratio coefficient is established by combining the subjective image quality evaluation and the image characteristic factor. The experimental test results show that the video image adaptive enhancement algorithm has good enhancement effect, good real-time performance, can effectively mine the dark vision information, and can be widely used in different scenes.

• Korean Institute of Interior Design Journal
• /
• v.19 no.6
• /
• pp.112-120
• /
• 2010

Human can recognize the environment by detecting spatial perception, and most of environmental perception depends on visual perception. In view that the acquisition of spatial information is accomplished through visual recognition, analysis of visual structure contained in the space is thought to be very important sector in studying the characteristic of the space. The history of studies on visual structure of space, however, wasn't too long, and furthermore most of the theories up to now focused on static and planar principles. Under this circumstance, this study is intended to suggest new theory by combining Isovist theory and VGA theory that have been actively discussed as the theory on visual perception-based spatial structure and supplementing them between each other to expand into 3-dimensional model. The suggested theory is a complex principle in dimensional and dynamic form in consideration of visual direction, which forms 3-dimentional virtual model that enables visualization of the property of spatial structure as the routine discriminating whether visual connection is made between viewing point and target point, and the target point is included in the visual field quadrangular pyramid or not. Such model was built up by an analysis application where four probe paths were applied to simulate the visual structure that occurs in virtual space, and then the characteristics were analyzed through quantification. In result, in spite of the path with equal space and equal length, significant difference in the acquired quantity of spatial information could be found depending on the probe sequence. On the contrary, it was found that probe direction may not affect the acquired quantity of information and visual property of the space.

• Korea Journal of Hospital Management
• /
• v.28 no.2
• /
• pp.1-8
• /
• 2023

Purpose: This study was conducted to identify the impact of human rights sensitivity and patient rights awareness of first-year students in clinical practice on clinical practice adaptation and to prepare practical and systematic personality development program education alternatives to foster high-quality medical personnel. Method: As for the research method, an online survey of 155 medical and nursing students from two universities in G-do (76 medical students and 79 nursing students) was conducted, and the collected data were T-test, ANOVA, Scheffe test, Pearson's correlation coefficient and step-by-step multiple regression analysis using SPSS WIN/25.0. Findings: The results of the study are as follows. First, as a result of analyzing the differences in each variable according to general characteristics, human rights sensitivity had a significant impact on gender, patient rights recognition on personality type, and clinical practice adaptation had a significant impact on major selection motivation. Second, the factors affecting the adaptation of first-year college students to clinical practice had a significant impact on extroverted personality and patient rights perception among personality types (regression model results F=6.38 (p<).001), 24.2% explanatory power). Conclusion: This study suggests that education and policy efforts are needed to foster accurate awareness of human rights issues by developing flexible and flexible extracurricular activity programs in the operation of the curriculum to strengthen medical and nursing students' ability to adapt to clinical practice and improve awareness of human rights issues.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.9 s.114
• /
• pp.897-903
• /
• 2006

The reduction of the vehicle interior noise has been the main interest of noise and vibration harshness (NVH) engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the heating, ventilation and air conditioning (HVAC) system sound among the vehicle interior noise has been reflected sensitively in psychoacoustics view point. Even though the HVAC noise is not louder than overall noise level, it clearly affects subjective perception to drivers in the way of making to be nervous or annoyed. Therefore, these days a vehicle engineer takes aim at developing sound quality as well as reduction of noise. In this paper, we acquired noises in the HVAC from many vehicles. Through the objective and subjective sound quality (SQ) evaluation with acquiring noises recorded by the vehicle HVAC system, the simple and multiple regression models were obtained for the subjective evaluation 'Pleasant' using the semantic differential method (SDM). The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Furthermore, the neural network (NN) model were obtained using three inputs(loudness, sharpness and roughness) of the SQ metrics and one output(subjective 'Pleasant'). Because human's perception is very complex and hard to estimate their pattern, we used NN model. The estimated models were compared with correlations between output indexes of SQ and hearing test results for verification data 'Pleasant'. As a result of application of the SQ indexes, the NN model was shown with the largest correlation of SQ indexes and we found possibilities to predict the SQ metrics.

• International journal of advanced smart convergence
• /
• v.1 no.1
• /
• pp.6-13
• /
• 2012

An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

• Journal of Engineering Education Research
• /
• v.26 no.6
• /
• pp.19-29
• /
• 2023

This study aims to develop and apply a metaverse-based instructional design model for the education in science and technology. It analyzed the concept and characteristics of metaverse, existing non-contact education models, and major teaching strategies systematically. Based on the prior researches, an instructional design model using metaverse is developed that presents metaverse-related teaching strategies and design principles for the before-, during-, and after-lesson phases. Then, this model was applied to a project-based learning program, conducted a perception survey on instructors and learners, and revised the metaverse instructional design model based on the results of the survey. In the Metaverse Instructional Design Model, before-lesson phase is a physical and psychological preparation stage for class participation, which includes familiarization with the Metaverse learning environment, formation of expectations for education, and self-directed pre-learning. During the lesson, to effectively deliver the lesson content, it is necessary to build confidence in the learning environment, promote learning participation, provide reference materials, perform team projects and provide feedback, digest learning content, and transfer learning content. The after-lesson phase provides strategies for ongoing interaction between learners and mentors. This study introduces a new instructional design model that utilizes metaverse and shows the potential of metaverse-based education in science and technology. It also has important implications in that it provides practical guidelines for the effective design and implementation of metaverse-based education.

• Korean Journal of Human Ecology
• /
• v.17 no.6
• /
• pp.1135-1149
• /
• 2008

The main purpose of this research was to examine a causal model concerning the direct and the indirect effect of family-of-origin functioning on psychological well-being through self-differentiation. The gender differences in the levels of the variables and the correlations among the variables were also examined. Participants were 587 female and 268 male students enrolled in nine different universities. The causal model was tested through structural equation model by using AMOS 8.0 program. The result showed that the levels of self-differentiation and psychological well-being were higher for males than for females, and that the three variables were positively associated to each other for both males and females. The result also indicated that male students' perception of family-of-origin functioning directly influenced their psychological well-being as well as indirectly through self-differentiation, while females' family-of-origin functioning had only a direct effect on their well-being. Results were discussed in terms of the applicability of self-differentiation to Korean college students and of the importance of family-of-origin functioning to improve students' mental health.