• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.32-34
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• 1997

For a given brushless DC linear motor, we suggest the numerical prediction methods to analyze it's thrust characteristics. First, we calculate the magnetic flux density by the finite element method, and we then compute the maximum thrust with three computational methods - a Lorentz equation, a Maxwell stress method and a virtual work method. To confirm the accuracy of the computational methods, we measure the thrust of the linear motor made by our laboratory with a force-torque sensor. Also, we calculate the thrust by the measured back electromotive force. To choose the appropriate method for a specified application, we compare the maximum thrusts of the computational method and the calculation by the back electromotive force with the measured one. We conclude that the Maxwell stress method is turned out the best because it has the most accurate results among three computational methods and it is more convenient than the calculation method by the back electromotive force.

• Journal of Korea Multimedia Society
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• v.21 no.1
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• pp.51-60
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• 2018

We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

• Journal of Mechanical Science and Technology
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• v.20 no.3
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• pp.297-309
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• 2006

This paper deals with a novel structure for single-cell characterization which makes use of bimorph micro thermal actuators combined with electrical sensor device and integrated microfluidic channel. The goal for this device is to capture and characterize individual biocell. Quantitative and qualitative characteristics of bimorph thermal actuator were analyzed with finite element analysis methods. Furthermore, optimization for the dimension of cantilevers and integrated parallel probe systems with microfluidic channels is able to be realized through the virtual simulation for actuation and the practical fabrication of prototype of probes. The experimental value of probe deflection was in accordance with the simulated one.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.67-72
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• 2015

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user's logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.255-261
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• 2007

We propose a optimal fusion method for localization of multiple robots utilizing correlation between GPS on each robot in common workspace. Each mobile robot in group collects position data from each odometer and GPS receiver and shares the position data with other robots. Then each robot utilizes position data of other robot for obtaining more precise estimation of own position. Because GPS data errors in common workspace have a close correlation, they contribute to improve localization accuracy of all robots in group. In this paper, we simulate proposed optimal fusion method of odometer and GPS through virtual robots and position data.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.393-397
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• 1997

본 연구에서는 손동작(Hand Motion)과 수작업(Manual Task) 분석에 VR환경에서 사용되는 각도 측정 장갑(3-D Glove)을 이용하는 방법을 제안하였다. 본 연구에서 개발된 손동작(Hand Motion)과 수작업(Manual Task)의 분석 시스템은 18-sensor $Cyberglove^{TM}$정 시스템으로부터 측정된 angle data를 기초로 손동작이나 수작업에 대한 totalmuscle moment값과 total muscle excursion값을 구하고, digit와 joint의 moment값을 X,Y.Z방향별고 구하는 기능을 가지고 있다. 시스템의 구성은 : (1) $Cyberglove^{TM}$ System과 분석 시스템의 digital data 처리를 기반으로 하는 손동작의 측정 시스템 ; (2) $Cyberglove^{TM}$ System에서 얻어진 자료를 바탕으로 3차원 공간에서 손동작을 표현할 수 있는 Kinematic Hand Model ; (3) Hand Model과 $Cyberglove^{TM}$ Systme을 기반으로 3차원에서 손동작의 역학적 분석을 할 수 있는 3-D Hand Biomechanical Model ; 등으로 되어있다. 본 시스템은 Telerobotics, Medicine, Virtual Reality 등 다양한 분야에 응용이 가능하며, 수작업에 관련되는 Product Design, Manual Control Device, Computer I/O Device의 설계에도 도움이 될 것으로 기대된다.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.937-943
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• 2016

Vertical velocity is critical in many areas, such as the control of unmanned aerial vehicles, fall detection, and virtual reality. Conventionally, the integration of GPS (Global Positioning System) with an IMU (Inertial Measurement Unit) was popular for the estimation of vertical components. However, GPS cannot work well indoors and, more importantly, has low accuracy in the vertical direction. In order to overcome these issues, IMU-barometer integration has been suggested instead of IMU-GPS integration. This paper proposes a new complementary filter for the estimation of vertical velocity based on IMU-barometer integration. The proposed complementary filter is designed to minimize drift error in the estimated velocity by adding PID control in addition to a zero velocity update technique.

• The Journal of the Korean dental association
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• v.56 no.6
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• pp.339-347
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• 2018

Conventional mouthguard fabrication process which consists of elastomeric impression taking and followed gypsum model making is changing into intraoral scanning and dental model printing with 3D printer. In addition, new 3D printing materials for mouthgurad, 3D Computer-Aided Design(CAD) software for dental appliance, evaluation of a virtual dentoalveolar model for testing virtually 3D designed mouthguard, and lightweight sensor technology will lead dental professionals to the new era of Sports Dentistry, including information technology integrated custom mouthguard fabrication and creating value with analytic data acquired from sensors in mouthguard.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.7
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• pp.385-392
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• 2003

A nonlinear speed controller for a separately excited DC motor (SEDCM) based on a newly developed adaptive backstepping approach is presented. To compensate parameter uncertainties and load torque disturbance, a nonlinear adaptive backstepping control law and adaptive law are derived systematically step by step through virtual control input and suitable Lyapunov function. Also, speed observer without using costly speed sensor is presented. Simulation results show that the proposed controller can observe real speed and track the reference speed signal generated by a reference model.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.