• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.57-58
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• 2018

The number of deaths in the korean construction industry is more than three times the OECD average. Although safety management system should be improved to prevent the safety accidents, it is difficult to improve due to domestic safety conditions. Especially, in order to prevent accidents at construction sites, there is an increasing tendency to monitor the movement of workers and equipment in real time by introducing a location positioning system. Therefore, this study proposes a system that can monitor the position of workers and heavy equipments in real - time, detect danger and transmit alarms so that workers can pay attention to safety and keep safety. The system is expected to reduce safety accidents by transmitting alarms to workers so that they can pay attention.

• Journal of IKEEE
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• v.22 no.3
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• pp.754-758
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• 2018

Analysis methods in the power system are static analysis, dynamic analysis and online analysis, offline analysis. The static analysis is used for the existing power system analysis method and the static analysis is mainly used for PSS / E. However, in the real system where the value changes in real time which we are using, dynamic analysis is required which can be analyzed in real time for accurate analysis. Therefore, attention is focused on EMS (Energy Management System) and importance is increasing. Among the various EMS systems, we will cover state estimation, which is a static on-line analysis that can receive and interpret data from the acquisition point in real time. DC systems are spreading in various fields such as DC load, DC distribution, renewable energy. As such, much attention and attention are focused on the DC system. In this paper, we have studied the feasibility through the case study and the interpretation of the state estimation that can be applied to the DC system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.90-101
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• 2012

The landmark selection is crucial to successful perform in SLAM(Simultaneous Localization and Mapping) with a mono camera. Especially, in unknown environment, automatic landmark selection is needed since there is no advance information about landmark. In this paper, proposed visual attention system which modeled human's vision system will be used in order to select landmark automatically. The edge feature is one of the most important element for attention in previous visual attention system. However, when the edge feature is used in complicated indoor area, the response of complicated area disappears, and between flat surfaces are getting higher. Also, computation cost increases occurs due to the growth of the dimensionality since it uses the responses for 4 directions. This paper suggests to use a corner feature in order to solve or prevent the problems mentioned above. Using a corner feature can also increase the accuracy of data association by concentrating on area which is more complicated and informative in indoor environments. Finally, this paper will prove that visual attention system based on corner feature can be more effective in SLAM compared to previous method by experiment.

• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.399-415
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• 2007

Many objects are always present in a visual scene. Since the visual system has limited capacity to process multiple stimuli at a time, how to cope with this informational overload is one of the important problems to solve in visual perception. This study investigated the suppressive interactions among multiple stimuli when attention was directed to either one of the stimuli or all of them. The results indicate that suppressive interactions among multiple circles were reduced in V4 when subjects paid attention to one of the four locations, as compared to the unattended condition. However, suppressive interactions were not reduced when they paid attention to all four items as a set, in order to compute their mean size. These results suggest that whereas focused attention serves to later out irrelevant information, distributed attention provides an average representation of multiple stimuli.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.182-189
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• 2023

Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.627-636
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• 2011

The purpose of this study is to develop the multi-modal interaction system. This system provides realistic and an immersive experience through multi-modal interaction. The system recognizes user behavior, intention, and attention, which overcomes the limitations of uni-modal interaction. The multi-modal interaction system is based upon gesture interaction methods, intuitive gesture interaction and attention evaluation technology. The gesture interaction methods were based on the sensors that were selected to analyze the accuracy of the 3-D gesture recognition technology using meta-analysis. The elements of intuitive gesture interaction were reflected through the results of experiments. The attention evaluation technology was developed by the physiological signal analysis. This system is divided into 3 modules; a motion cognitive system, an eye gaze detecting system, and a bio-reaction sensing system. The first module is the motion cognitive system which uses the accelerator sensor and flexible sensors to recognize hand and finger movements of the user. The second module is an eye gaze detecting system that detects pupil movements and reactions. The final module consists of a bio-reaction sensing system or attention evaluating system which tracks cardiovascular and skin temperature reactions. This study will be used for the development of realistic digital entertainment technology.

• Proceedings of the Safety Management and Science Conference
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• 2008.04a
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• pp.259-271
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• 2008

In the information society where knowledge plays a significant role, the value of the corporate organization creates knowledge strategically and spreads it to the whole organization so as to reinforce the efficiency of the work force. After KMS was recognized as one of core competences of company, KMS based on information technology has been introduced actively to many corporate organizations for the implementation of realizing knowledge management. As the strategic use of KMS increases in company, it has attracted attention to the system and the investment in the system, now attention has brought to the effect of the system. The efficiency and effectiveness of KMS has been tackled as one of the most important issues, and then many studies have been implemented to measure the result of the system. The purpose of this study is to overcome these problems and to help make an important decision in establishing introduction strategy by abstracting the reasons and success factors and result indices which are important sources for introducing KMS.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.119-128
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• 2022

Recently, due to the development of related technologies for autonomous vehicles, driving work is changing more safely. However, the development of support technologies for level 5 full autonomous driving is still insufficient. That is, even in the case of an autonomous vehicle, the driver needs to drive through forward attention while driving. In this paper, we propose a method to monitor driving tasks by recognizing driver behavior. The proposed method uses pre-trained deep convolutional neural network models to recognize whether the driver's face or body has unnecessary movement. The use of pre-trained Deep Convolitional Neural Network (DCNN) models enables high accuracy in relatively short time, and has the advantage of overcoming limitations in collecting a small number of driver behavior learning data. The proposed method can be applied to an intelligent vehicle safety driving support system, such as driver drowsy driving detection and abnormal driving detection.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.17 no.2
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• pp.163-169
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• 2006

Objectives : The study was conducted to investigate the effect of intelligence ability on attention using Continuous Performance Test (CPT). Methods : 56 children with ADHD (52 boys, 4 girls) and 41 children in normal (28 boys, 13 girls) were sampled, their age range was 7 to 15. They performed IQ test and ADHD Diagnostic System (ADS) in order to examine intelligence and attention. Participants were divided into normal group and ADHD group, average IQ level children and superior IQ level children. Then ADS variables (omission error, commission error, reaction time, reaction time deviation, response sensitivity, and response criterion) were analyzed. Results : There was no significant interaction effect between group (normal, ADHD) and intelligence (average, superior). But there was significant difference between normal group and ADHD group in omission error, commission error, reaction time deviation, and response sensitivity. Also average level IQ group had significantly showed more omission, greater reaction time deviation, and lower response sensitivity than superior level IQ group. Conclusion : ADHD group has attention deficit than normal group, and CPT is available tool to detect attention problems. These findings indicate that intelligence can contaminate inattention and cognitive impulsivity thus it compensates for attention deficit. And it suggests that intelligence effect is considered in analyzing CPT in ADHD children.

• Journal of the Korean Society of School Health
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• v.23 no.2
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• pp.237-245
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• 2010

Purpose: The purpose of this thesis was to examine the effects of social skills training program onto the children with tendency of attention-deficit hyperactivity disorder. Methods: This study used nonequivalent control group pre/post-test quasi-experimental research design. The subjects were 18 children with tendency of attention- deficit hyperactivity in D City. The subjects were divided into two groups, an experimental group of 8 children and a control group of 10. The program consisted of 20 sessions of 60 minutes per session, 5 days a weeks, for 4 weeks. The research tools included Conner's Teacher Rating Scales (CTRS) and Social Skills Rating System (SSRS). The collected data were analyzed using $x^2$ test, Mann-Whitney test on the SPSS 17.0 program. Results: a) the scores for cooperation, self-assertiveness, self-control and empathy increased significantly in the experimental group, compared to the control group. b) the scores for social skills increased significantly in the experimental group, compared to the control group. Conclusion: It appears that the social skills training program is a useful nursing intervention to improve the social skills for children with tendency of attention-deficit hyperactivity.