• Journal of Environmental Health Sciences
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• v.50 no.1
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• pp.6-15
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• 2024

Background: People's activities have been restricted due to the COVID-19 pandemic. These changes in activity patterns may lead to a decrease in fine particulate matter (PM_2.5) concentrations. Additionally, the level of population exposure to PM_2.5 may be changed. Objectives: This study aimed to analyze the impact of population movement and meteorological factors on the distribution of PM_2.5 concentrations before and after the outbreak of COVID-19. Methods: The study area was Guro-gu in Seoul. The research period was selected as January to March 2020, a period of significant population movement changes caused by COVID-19. The evaluation of the dynamic population was conducted by calculating the absolute difference in population numbers between consecutive hours and comparing them to determine the daily average. Ambient PM_2.5 concentrations were estimated for each grid using ordinary kriging in Python. For the population exposure assessment, the population-weighted average concentration was calculated by determining the indoor to outdoor population for each grid and applying the indoor to outdoor ratio to the ambient PM_2.5 concentration. To assess the factors influencing changes in the ambient PM_2.5 concentration, a statistical analysis was conducted, incorporating population mobility and meteorological factors. Results: Through statistical analysis, the correlation between ambient PM_2.5 concentration and population movement was positive on both weekends and weekdays (r=0.71, r=0.266). The results confirmed that most of the relationships were positive, suggesting that a decrease in human activity can lead to a decrease in PM_2.5 concentrations. In addition, when population-weighted concentration averages were calculated and the exposure level of the population group was compared before and after the COVID-19 outbreak, the proportion of people exceeding the air quality standard decreased by approximately 15.5%. Conclusions: Human activities can impact ambient concentrations of PM_2.5, potentially altering the levels of PM_2.5 exposure in the population.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.215-224
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• 2011

There have been studying many researches to detect human body and to track one with increasing interest on human and computer interaction. In this paper, we propose the algorithm that automatically extracts joints, linked points of human body, using the ratio of human body under single camera and tracks object. The proposed method gets the difference images of the grayscale images and ones of the hue images between input image and background image. Then the proposed method composes the results, splits background and foreground, and extracts objects. Also we standardize the ratio of human body using face' length and the measurement of human body and automatically extract joints of the object using the ratio and the corner points of the silhouette of object. After then, we tract the joints' movement using block-matching algorithm. The proposed method is applied to test video to be acquired through a camera and the result shows that the proposed method automatically extracts joints and effectively tracks the detected joints.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1070-1075
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• 2013

In this research, we describe a security robot system and ongoing research results to control human's wrong direction in order to forbid human to enter security zone. Proposed robot system surveils a security area with equipped laserscanner sensor usually. When it detect walking human who is for the area, robot calculates his velocity vector, plans own path to forestall and interrupts him who want to head restricted area and starts to move along the estimated trajectory. The walking human is assumed to be a point-object and projected onto an scanning plane to form a geometrical constraint equation that provides position data of the human based on the kinematics of the mobile robot. While moving the robot continues these processes for adapting change of situation. After arriving at an opposite position human's walking direction, the robot advises him not to be headed more and change his course. The experimental results of estimating and tracking of the human in the wrong direction with the mobile robot are presented.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1049-1056
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• 2024

Human-robot collaboration (HRC) is an emerging form of work anticipated to improve construction productivity by integrating robotic capabilities with human expertise. With the expected transition towards tasks that demand more cognitive efforts for human workers, considering the cognitive status of each co-worker, such as task engagement and vigilance, can become crucial to achieve high-quality human performance during HRC, potentially contributing to a more productive HRC in construction. However, the potential cognitive changes of each co-worker have remained unclear during HRC, as studies have primarily focused on identifying general trends from aggregated cognitive responses of people, in which an individual's response can be overlooked. In this study, we examine the cognitive response of each co-worker during HRC for a construction task. We observed the cognitive responses of 18 people while they were experiencing different collaborating conditions, such as the robot's different movement speed, during a bricklaying task with an arm-type collaborative robot. For each participant, we analyzed electroencephalogram (EEG) signals to identify the changes in cognitive status by using a wearable EEG headset. The results present that the cognitive responses of almost all the participants were significantly and differently affected during HRC, impacting the estimated productivity of their human-robot teams. The findings of the study present the importance of considering each co-worker's potentially unique cognitive response as a way to achieve cognitive wellbeing while pursuing high productivity within human-robot teams, potentially contributing to overall productive HRC in construction.

• International Journal of Contents
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• v.6 no.2
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• pp.14-20
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• 2010

Korean Cultural Content Industry is developing creative cultural content based on internationally acknowledged manufacturing capacity, however, in order to become cultural industry with international competitiveness, it has to be planned and made in OMSU way. This research studied and analyzed successful cases of cultural content digital restoration and excellent cases of OSMU-type that has been developed and supported by Korean Culture and Contents Agency. This study suggests the direction of growth on the basis of movement of cultural content industry and cultivating plan of human resources.

• Journal of the Ergonomics Society of Korea
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• v.19 no.1
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• pp.63-76
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• 2000

In this study, the factors affecting reality aspect of virtual reality system were identified through Quality Function Deployment. The influence of some selected factors was evaluated in simulated performance test. It was shown that the factor of whether user can break through the objects in virtual space is the most sensitive to performance, followed by the factors of rotation angle and movement step. Also, the results implied that as more referents were provided to user, feeling of reality was enhanced.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.825-827
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• 1997

This paper presents a robot which is steered by vision system. The proposed robot system has an AM188ES CPU(5.3 MIPS) and 2DC motors with encoder and turns accurately at any speed and shows a movement like a human controlled car using a steering wheel. To the robot only steering angle value is sent without considering the speed. We present how to control this robot using our real time vision system.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.466-469
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• 2002

게임이나 가상현실에서 캐릭터의 보행 동작의 움직임은 일정한 동작만을 생성하여 가상공간에 표현한다. 지형이나 다른 주변 환경에 의한 적응적인 동작을 실시간으로 자동 생성하는데 있어서 자연스러운 동작을 표현하기에는 매우 어려움이 따른다. 본 논문에서는 지질에 따른 캐릭터의 걷기 동작을 생성하는 방법에 대해 제안한다. 우선 캐릭터의 기본 걷기 동작 생성은 inverse kinematics방법을 적용하고, 지형 성질을 분석하여 이를 캐릭터의 걷기 동작 생성하는데 적용한다.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.149-153
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• 1989

This paper investigates the possibility of applying fuzzy algorithms to the collision avoidance problem of a cylindrical robot moving in a 3-dimensional workspace. The displacement information from the end-effector to the points via which the robot can avoid collisions is given by the human operator. Then this uncertain information is adopted for the fuzzy inference system for robot movements. The robot movement is simulated to verify the effectiveness of the proposed fuzzy algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.232-234
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• 2002

EEG-based brain computer interface (BCI) provides a new communication channel between human brain and computer. The classification of EEG data is an important task in EEG-based BCI. In this paper we present methods which jointly employ principal component analysis (PCA) and linear dynamical system (LDS) modeling for the task of EEG classification. Experimental study for the classification of EEG data during imagination of a left or right hand movement confirms the validity of our proposed methods.