• Journal of the Korean Society for Precision Engineering
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• v.21 no.5
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• pp.64-72
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• 2004

An extension of interaction matrix formulation to the problem of system and disturbance identification for a plant that is corrupted by both process and output disturbances is presented. The teaming control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of loaming control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. This paper studies the use of such controllers in a decentralized system, such as a robot moving on the vertical plane with the controller for each link acting independently. The basic result of the paper is to show that stability and iterative precision of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized teaming in the coupled system, provided that the sample time in the digital teaming controller is sufficiently short. The methods of teaming system are shown up for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.1
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• pp.193-198
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• 2005

Changes in visuospatial cognitive performance, blood oxygen saturation and heart rate due to the highly concentrated oxygen administration were observed in this study. Six male ($25.8 \pm$1.0) and six female (($23.8 \pm$ 1.9) adults were asked to perform 20 visuospatial tasks with the same level of difficulties by supplying two different oxygen levels (21%, 30%). Experiment consisted of Rest1 (1 min.), Control (1 min.), Task (4 min.), and Rest2 (4 min.) and physiological signals such as blood oxygen saturation and heart rate were measured through each stage. The result showed the accuracy of task performance increased significantly at 30% oxygen concentration compared with 21%, which means oxygen supply has positive effects on visuospatial cognitive performance. When 30% oxygen was supplied, blood oxygen saturation during control and task phases was increased and heart rate was decreased compared with 21%. It means that 30% oxygen can stimulate brain activities by directly increasing the actual level of blood oxygen concentration during cognitive performance, and enough oxygen supply during cognitive performance make heart rate decrease.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.206-215
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• 1996

Recently, proportion of the aged becomes greater in Korea like the advanced country as time passed away, and this is treated as one of major social problems. Therfore, we investigated visual/auditory signal detection performance to evaluate vocational aptitude of the middle-and old-aged workers in this study. It was shown that signal detection performance decreased as workers became older, and there was large individual difference in signal detection performance. Since signal detection performance in visual task decreased rapidly and more than that in auditory task, the middle-and old-aged workers can not carry out properly visual inspection and precision task was related with that in auditory task. It can be expected that the parameters used in this study are in good use for evaluating a worker's aptitude.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.101-108
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• 2004

An electro-hydraulic manipulator using hydraulic actuators has many nonlinear elements, and its parameter fluctuations are greater than those of an electrically driven manipulator. So it is relatively difficult to obtain stable control performance. In this report, we applied disturbance estimation and compensation type robust control to all axes in a 3-link electro-hydraulic manipulator. From the results of experiment, it was confirmed that the performance of trajectory tracking and attitude regulating is greatly improved by the disturbance observer, which model is the same for each axis. On the other hand, for the autonomous assembly tasks, it is said that compliance control is one of the most available methods. Therefore we proposed compliance control which is based on the position control by disturbance observer for our manipulator system. To realize more stable contact work, the states in the compliance loop are feedback, where not only displacement but also velocity and acceleration are considered. And we applied this compliance control to Peg-in-Hole insertion task and analyzed mechanical relation between peg and hole. Also we proposed new method of shifting the position of end-effector periodically for the purpose of smooth insertion. As a result of using this method, it is experimentally confirmed that Peg-in-Hole insertion task with a clearance of 0.05［mm］can be achieved.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.273-282
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• 2022

MPEG-VCM(Video Coding for Machine) aims to standardize video codec for machines. VCM provides data sets and anchors, which provide reference data for comparison, for several machine vision tasks including object detection, object segmentation, and object tracking. The evaluation template can be used to compare compression and machine vision task performance between anchor data and various proposed video codecs. However, performance comparison is carried out separately for each machine vision task, and information related to performance evaluation of multiple machine vision tasks on a single bitstream is not provided currently. In this paper, we propose a performance evaluation method of a video codec for AI-based multi-tasks. Based on bits per pixel (BPP), which is the measure of a single bitstream size, and mean average precision(mAP), which is the accuracy measure of each task, we define three criteria for multi-task performance evaluation such as arithmetic average, weighted average, and harmonic average, and to calculate the multi-tasks performance results based on the mAP values. In addition, as the dynamic range of mAP may very different from task to task, performance results for multi-tasks are calculated and evaluated based on the normalized mAP in order to prevent a problem that would be happened because of the dynamic range.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4080-4097
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• 2020

In recent years, convolutional neural network (CNN) has become the primary method for face detection. But its shortcomings are obvious, such as expensive calculation, heavy model, etc. This makes CNN difficult to use on the mobile devices which have limited computing and storage capabilities. Therefore, the design of lightweight CNN for face detection is becoming more and more important with the popularity of smartphones and mobile Internet. Based on the CPU real-time face detector FaceBoxes, we propose a multi-task lightweight face detector, which has low computing cost and higher detection precision. First, to improve the detection capability, the squeeze and excitation modules are used to extract attention between channels. Then, the textual and semantic information are extracted by shallow networks and deep networks respectively to get rich features. Finally, the landmark detection module is used to improve the detection performance for small faces and provide landmark data for face alignment. Experiments on AFW, FDDB, PASCAL, and WIDER FACE datasets show that our algorithm has achieved significant improvement in the mean average precision. Especially, on the WIDER FACE hard validation set, our algorithm outperforms the mean average precision of FaceBoxes by 7.2%. For VGA-resolution images, the running speed of our algorithm can reach 23FPS on a CPU device.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.8
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• pp.180-187
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• 2004

The present study attempted to investigate the effects of supply of highly concentrated (30%) oxygen on human ability of visuospatial cognition and cerebrum lateralization. compared to air of normal oxygen concentration (21%). The experiment consisted of two runs, one fur visuospatial cognition test with normal air (21% of oxygen) and for visuospatial cognition test with more oxygen in the air (30% of oxygen). Each run was composed of four blocks and each block included eight control tasks and five visuospatial tasks. Functional brain images were taken from 3T MRI using the single-shot EPI method. The result of task performance showed the accuracy increased at 30%＇s concentration of oxygen rather than 21%＇s. There were more activations observed at the left and right hemisphere, but there was decrease cerebrum lateralization with 30% oxygen administration. Thus, it is concluded that the positive effect on the visuospatial cognitive performance level by the highly concentrated oxygen administration was due to increase of cerebrum activation and decrease of cerebrum lateralization

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.126-137
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• 1994

Performance management of computer networks is intended to improve a given network performance in order for more efficient information exchange between subsystems of an integrated large-scale system. Importance of perfomance management is growing as many functions of the large- scale system depend on the quality of communication services provided by the network. The role of performance management is to manipulate the adjustable protocol parameters on line so that the network can adapt itself to a dynamic environment. This can be divided into two subtasks : performance evaluation to find how changes in protocol parameters affect the network performance and decision making to determine the magnitude and direction of parameter adjustment. This paper is the first part of the two papers focusing on conceptual design, development, and evaluation of performance management for token bus networks. This paper specifically deals with the task of performance evaluation which utilizes the principle of perturbation analysis of discrete event dynamic systems. The developed algorithm can estimate the network performance under a perturbed protocol parameter setting from observations of the network operations under a nominal parameter setting.