• Journal of the Ergonomics Society of Korea
• /
• v.36 no.5
• /
• pp.373-383
• /
• 2017

Objective: The aim of this study is to introduce an operator console design review system suitable for designing and evaluating consoles based on human factor guidelines for a digitalized main control room in an advanced nuclear power plant which has a requirement for anthropometric data usage. Background: The system interface of the main control room in a nuclear power plant has been getting digitalized and consists of various consoles with many information displays. Console operators often face human-computer interactive problems due to inappropriate console design stemming from the perceptual constraints of anthropometric data usage. Method: Computational models with a process of visual perception and variables of anthropometric data are used for designing and evaluating operator consoles suitable for human system interface guidelines, which are used in an advanced nuclear power plant. Results: From the computational model and simulation application, console dimensions and a designing test module, which would be used for designing suitable consoles with safety concerns in a nuclear power plant, have been introduced. Conclusion: This case study may influence employing a suitable design concept with various anthropometric data in many areas with safety concerns and may show a feasible solution to designing and evaluating the safety console dimensions. Application: The results of this study may be used for designing a control room with the human factors requiring a safe working environment.

• Archives of design research
• /
• v.17 no.2
• /
• pp.23-32
• /
• 2004

This paper's objective is the analysis of eye-movement recording with visual perception process, the inference of heuristic guidelines with human information processing, and the generation of design principles for practical works. For this objective, it was experimented on that the user's eye-movement recording of interactive media with the Eyegaze Interface System, and analyzed the visual perception process of top-down & bottom-up processing, and inferred the design principles from human information process. Our results provide the implications of design through the analysis of the user's eye-movement recording that were changed according to each menu depth of the interactive media. And, it is proposed that the new concept of heuristic guidelines based on each stage of action that is related to human factors.

• ETRI Journal
• /
• v.35 no.5
• /
• pp.859-868
• /
• 2013

The active noise control (ANC) technique attenuates acoustic noise in a flexible and effective way. Traditional ANC design aims to minimize the residual noise energy, which is indiscriminative in the frequency domain. However, human hearing perception exhibits selective sensitivity for different frequency ranges. In this paper, we aim to improve the noise attenuation performance in perceptual perspective by incorporating noise weighting into ANC design. We also introduce psychoacoustic analysis to evaluate the sound quality of the residual noise by using a predictive pleasantness model, which combines four psychoacoustic parameters: loudness, sharpness, roughness, and tonality. Simulations on synthetic random noise and realistic noise show that our method improves the sound quality and that ITU-R 468 noise weighting even performs better than A-weighting.

• Journal of Digital Convergence
• /
• v.14 no.8
• /
• pp.555-564
• /
• 2016

Space perception is generally treated as a problem relevant to the ability to recognize objects. Alternatively, the data from shape perception studies contributes to discussions about the geometry of visual space. This geometry is generally acknowledged not to be Euclidian, but instead, elliptical, hyperbolic or affine, which is to say, something that admits the distortions found in so many shape perception studies. The purpose of this review article is to understand perceived shape and the geometry of visual space in the context of visually guided action. Thus, two prominent approaches that explain the relation between perception and action were compared. It is important to understand the fundamental information of how human perceive visual space and perform visually guided action for the convergence on embodied cognition, and further on artificial intelligence researches.

• Nuclear Engineering and Technology
• /
• v.53 no.3
• /
• pp.825-832
• /
• 2021

A simulation-based approach is proposed to study the protective actions taken by residents during nuclear emergencies using cognitive findings. Human perception-based behaviors are not heavily incorporated in the evacuation study for nuclear emergencies despite their known importance. This study proposes a generic framework of perception-based behavior simulation, in accordance with the ecological concept of affordance theory and a formal representation of affordance-based finite state automata. Based on the generic framework, a simulation model is developed to allow an evacuee to perceive available actions and execute one of them according to Newton's laws of motion. The case of a shadow evacuation under nuclear emergency is utilized to demonstrate the applicability of the proposed framework. The illustrated planning algorithm enables residents to compute not only prior knowledge of the environmental map, but also the perception of dynamic surroundings, using widely observed heuristics. The simulation results show that the temporal and spatial dynamics of the evacuation behaviors can be analyzed based on individual perception of circumstances, while utilizing the findings in cognitive science under unavoidable data restriction of nuclear emergencies. The perception-based analysis of the proposed framework is expected to enhance nuclear safety technology by complementing macroscopic analyses for advanced protective measures.

• Journal of the Korean Society of School Health
• /
• v.36 no.3
• /
• pp.113-125
• /
• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• Journal of Internet Computing and Services
• /
• v.15 no.4
• /
• pp.9-20
• /
• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• Proceedings of the Korean Institute of Interior Design Conference
• /
• 1999.04a
• /
• pp.61-64
• /
• 1999

Environmental design should be based on the positive theory, a researcher structured symbolic aesthetics on the basis of positive perception theory. Symbolic aesthetics by ecological theory of perception, human preference is related to existence and the formation of place-identity and cognitive map is dealt importantly in this study. Symbolic aesthetics is a study on environmental meaning and a researcher understood the operation of environmental meaning by regarding symbology as a methodological frame and defined architecture as a visual language system after discussing the importance of signified.

• Journal of the Korean Society of Safety
• /
• v.24 no.1
• /
• pp.69-77
• /
• 2009

This paper reports the aging driver traffic accident severity modeling results. For the modeling, Poisson regression approach is applied using the data set obtained from the Korea Transportation Safety Authority's simulator-based driver aptitude test results. The test items include the estimations of moving objects' speed and stopping distance, drivers' multi-task capability, and kinetic depth perception and so on. The resulting model with the response variable of equivalent property damage only(EPDO) indicated that EPDO is significantly influenced by moving objects' speed estimation and drivers' multi-task capabilities. More interestingly, a comparison with the younger driver model revealed that the degradation of such capabilities may result in severer crashes for older drivers as suggested by the higher estimated parameters for the older driver model.

• Journal of Biomedical Engineering Research
• /
• v.14 no.1
• /
• pp.63-72
• /
• 1993

In this paper, the effect of background grey levels on the visual perception of target image displayed on CRT monitor has been investigated. The purpose of this study is to investigate the efficacy of CRT monitor as a display medium of image Information especially in medical imaging field. Tllree sets of experiments have been performed in this study : the first was to measure the luminance response of CRT monitor and to find the best fitting equation, and the second was the psychophysical experiment measuring the threshold grey level differences between the target image and the background required for visual discrimination (or various background grey levels, and the third was to develop a visual model that is predictable of the threshold grey level difference measured in the psychophysical experiment. The result of psycophysical experiment shows that the visual perception performance is significantly degraded in the range of grey levels lower than 50, which is turned out due to she low luminance change of CRT monitor in this range while human eye has been adapted lo relatively bright ambient illumination. And it Is also shown in the simulation study using the developed visual model that the dominant factor degrading the visual performance is the reflected light from the monitor surface by ambient light in general illumination condition.