• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.3 no.2
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• pp.5-16
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• 1999

We introduce a new projector for accelerating convergence of a symmetric eigenvalue problem Ax = x, and devise a power/Lanczos hybrid algorithm. Acceleration can be achieved by removing the hard-to-annihilate nonsolution eigencomponents corresponding to the widespread eigenvalues with modulus close to 1, by estimating them accurately using the Lanczos method. However, the additional Lanczos results can be obtained without expensive matrix-vector multiplications but a very small amount of extra work, by utilizing simple power-Lanczos interconversion algorithms suggested. Numerical experiments are given at the end.

• Journal of KSNVE
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• v.9 no.4
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• pp.769-777
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• 1999

Research on vibration of a vehicle with a transversely mounted 4-cylinder engine was performed using a vector synthesis method, Data of the engine vibration for the vector synthesis method was obtained experimentally and the data was ODS-fitted to calculate vibration level on any engine location assuming that the engine is rigid body in the frequency range of interest. In order to derive the excitation force on the vehicle body, the displacements were converted from the acceleration of engine. The transfer functions from engine mounts to toe pan on the floor were obtained experimentally. The vibration level on the toe pan was predicted by multiplying the excitation force by the transfer function. The predicted vibration level was compared with experimental data and the result was reasonable. Using the developed method, analysis was made for the effect of body fixture conditions of the vehicle when testing the engine vibration and for the effect of the transfer functions when the engine is installed or when the engine is removed. Finally the degree of contribution for 12 transfer paths was calculated.

• Structural Engineering and Mechanics
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• v.15 no.3
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• pp.299-314
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• 2003

This investigation presents an efficient method for identifying modal characteristics from the measured displacement, velocity and acceleration signals of multiple channels on structural systems. A Vector Backward Auto-Regressive model (VBAR) that describes the relationship between the output information in different time steps is used to establish a backward state equation. Generally, the accuracy of the identified dynamic characteristics can be improved by increasing the order of the Auto-Regressive model (AR) in cases of measurement of data under noisy circumstances. However, a higher-order AR model also induces more numerical modes, only some of which are the system modes. The proposed VBAR model provides a clear characteristic boundary to separate the system modes from the spurious modes. A numerical example of a lumped-mass model with three DOFs was established to verify the applicability and effectiveness of the proposed method. Finally, an offshore platform model was experimentally employed as an application case to confirm the proposed VBAR method can be applied to real-world structures.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.1
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• pp.78-86
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• 1998

This paper presents a numerical method of the minimum-time trajectory planning for a robot manipulator amid obstacles. Each joint displacement is represented by the linear combination of the finite-term quintic B-splines which are the known functions of the path parameter. The time is represented by the linear function of the same path parameter. Since the geometric path is not fixed and the time is linear to the path parameter, the coefficients of the splines and the time-scale factor span a finite-dimensional vector space, a point in which uniquely represents the manipulator motion. The displacement, the velocity and the acceleration conditions at the starting and the goal positions are transformed into the linear equality constraints on the coefficients of the splines, which reduce the dimension of the vector space. The optimization is performed in the reduced vector space using nonlinear programming. The total moving time is the main performance index which should be minimized. The constraints on the actuator forces and that of the obstacle-avoidance, together with sufficiently large weighting coefficients, are included in the augmented performance index. In the numerical implementation, the minimum-time motion is obtained for a planar 3-1ink manipulator amid several rectangular obstacles without simplifying any dynamic or geometric models.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.6
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• pp.534-542
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• 2005

This paper proposes the fuzzy logic based vector control method for a Surface Mounted Permanent Magnet Synchronous Motor(SMPMSM) used in the elevators. The gain of a conventional PI speed controller in the elevator drive system can not be usually set high due to mechanical resonances, therefore its performance becomes deteriorated. There have been many methods to solve above problems such as an acceleration feedback in the speed controller. However, the above methods have defects that parameter information is demanded. In this paper', a Fuzzy controller(FC) is adopted in the elevator drive system. The performance of a fuzzy controller is compared with a PI controller in the no load and load conditions by simulation and experiments.

• Journal of the Korea Society of Computer and Information
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• v.19 no.5
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• pp.43-52
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• 2014

In this paper, we propose Gravity Removal and Vector Rotation algorithm for counting steps of wearable device, and we evaluated the proposed GRVR algorithm with Micro-Electro-Mechanical (MEMS) 3-axis accelerometer equipped in low-power wearable device while the device is mounted on various positions of a walking or running person. By applying low-pass filter, the gravity elements are canceled from acceleration on each axis of yaw, pitch and roll. In addition to DC-bias removal and the low-pass filtering, the proposed GRVR calculates acceleration only on the yaw-axis while a person is walking or running thus we count the step even if the wearable device's axis are rotated during walking or running. The experimental result shows 99.4% accuracies for the cases where the wearable device is mounted in the middle and on the right of the belt, and 91.1% accuracy which is more accurate than 83% of commercial 3-axis pedometer when worn on wrist for the case of axis-rotation.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.684-691
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• 2006

As many functionalities such as cameras and MP3 players are converged to mobile phones, more intuitive and interesting interaction methods are essential. In this paper, we present applications and their enabling technologies for gesture interactive cell phones. They employ gesture recognition and real-time shake detection algorithm for supporting motion-based user interface and entertainment applications respectively. The gesture recognition algorithm classifies users' movement into one of predefined gestures by modeling basic components of acceleration signals and their relationships. The recognition performance is further enhanced by discriminating frequently confusing classes with support vector machines. The shake detection algorithm detects in real time the exact motion moment when the phone is shaken significantly by utilizing variance and mean of acceleration signals. The gesture interaction algorithms show reliable performance for commercialization; with 100 novice users, the average recognition rate was 96.9% on 11 gestures (digits 1-9, O, X) and users' movements were detected in real time. We have applied the motion understanding technologies to Samsung cell phones in Korean, American, Chinese and European markets since May 2005.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1557-1563
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• 2016

According to recent studies, poor sitting posture of the spine has been shown to lead to a variety of spinal disorders. For this reason, it is important to measure the sitting posture. We proposed a strategy for classification of sitting posture using machine learning. We retrieved acceleration data from single tri-axial accelerometer attached on the back of the subject's neck in 5-types of sitting posture. 6 subjects without any spinal disorder were participated in this experiment. Acceleration data were transformed to the feature vectors of principle component analysis. Support vector machine (SVM) and K-means clustering were used to classify sitting posture with the transformed feature vectors. To evaluate performance, we calculated the correct rate for each classification strategy. Although the correct rate of SVM in sitting back arch was lower than that of K-means clustering by 2.0%, SVM's correct rate was higher by 1.3%, 5.2%, 16.6%, 7.1% in a normal posture, sitting front arch, sitting cross-legged, sitting leaning right, respectively. In conclusion, the overall correction rates were 94.5% and 88.84% in SVM and K-means clustering respectively, which means that SVM have more advantage than K-means method for classification of sitting posture.

• Journal of Korea Game Society
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• v.14 no.3
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• pp.55-62
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• 2014

In particle-based fluid simulation, applying sudden power to particle raise unnatural flow when wave is breaking. To solve this problem, we have used an linear interpolation technique that interpolate between fluid particle by subdividing the time interval in the previous work. Acceleration vector of the particle with increased pressure in boundary could change smoothly. However, particle looks like flow with viscosity because the number of the minimum samples to interpolate increases. We propose an weighted-interpolation technique to represent the realistic movement of fluid. it is accumulating that has added and assigned different weights to the previous acceleration vector and current one repeatedly. weighted-interpolation technique using less minium samples to flow than linear interpolation, so it can solve the problem which particle looks like flow with viscosity.

• Development and Reproduction
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• v.7 no.1
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• pp.35-40
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• 2003

Gonadotropin releasing hormone(GnRH), which is secreted from the hypothalamus, has a pivotal role in the reproduction of mammals. Golden hamsters are seasonal breeding mammal and their sexual activity is determined by photoperiod(length of light per day). Long photoperiod(LP, $\leq$ 12.5 hours of light) maintains the reproductive activity and short photoperiod(SP, $\leq$ 12 hours of light) suppresses it. In order to investigate in detail, the sexual activity was individually examined in SP-housed male golden hamsters received a vector at three different concentrations which contains rat GnRH cDNA. The gonadal regression was significantly(P<0.05) accelerated by the highest concentrations of the vector at 8 and 10 weeks after the treatment in comparison to the other groups. In the light of pulsatile release of GnRH in maintaining reproductive activity, the vector containing GnRH cDNA might secrete the GnRH in a constant high level. These results suggest that the GnRH-containing vector might desensitize the anterior pituitary, leading to acceleration or testicular regression.