• The Transactions of the Korea Information Processing Society
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• v.7 no.9
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• pp.2994-3001
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• 2000

In this paper. a method for color image segmentation using region merging is proposed. A inhomogeneity which exists in image is reduced by smoothing with non-linear filtering. saturation enhancement and intensity averaging in previous step of image segmentation. and a similar regions are segmented by non-uniform quantization using zero-crossing information of color histogram. A edge strength of initial region is measured using high frequency energy of wavelet transform. A candidate region which is merged in next step is selected by doing this process. A similarity measure for region merging is processed using Euclidean distance of R. G. B color channels. A Proposed method can reduce an over-segmentation results by irregular light sources et. al, and we illustrated that the proposed method is reasonable by simulation.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.63-75
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• 2002

To improve the efficiency of the electric power generation, monthly maximum electric power consumptions for a next one year should be forecasted in advance and used as the fundamental input to the yearly electric power-generating master plan, which has a greatly influence upon relevant sub-plans successively. In this paper, we analyze the past 22-year hourly maximum electric load data available from KEPCO(Korea Electric Power Corporation) and select necessary data from the raw data for our model in order to reflect more recent trends and seasonal components, which hopefully result in a better forecasting model in terms of forecasted errors. After analyzing the selected data, we recommend to KEPCO the Winters' multiplicative model with decomposition and exponential smoothing technique among many candidate forecasting models and provide forecasts for the electric power consumptions and their 95% confidence intervals up to December of 1999. It turns out that the relative errors of our forecasts over the twelve actual load data are ranged between 0.1% and 6.6% and that the average relative error is only 3.3%. These results indicate that our model, which was accepted as the first statistical forecasting model for monthly maximum power consumption, is very suitable to KEPCO.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.3
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• pp.113-120
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• 2018

PURPOSE: This study was conducted to investigate the characteristics of a specific functional shoe in terms of the range of motion (ROM) of ankle and foot joints during walking when compared to a standardized shoe. METHODS: Kinematic ROM data pertaining to ankle, tarsometatarsal, and metatarsophalangeal joints were collected from twenty-six healthy individuals during walking using a ten-camera motion analysis system. Kinematic ROM of each joint in three planes was obtained over ten walking trials consisting of two different shoe conditions. Visual3D motion analysis was finally used to coordinate the kinematic data. All kinematic ROM data were interpolated using a cubic spline algorithm and low-pass filtered with a cutoff frequency of 6 Hz for smoothing. RESULTS: The overall ROM of the ankle joint in the sagittal and coronal planes when wearing the specific functional shoe was significantly decreased in both ankles during walking when compared to wearing a standard shoe (p<.05). Significantly more flexibility was observed when wearing the specific functional shoe in the tarsometatarsal and metatarsophalangeal joints compared to a standard shoe (p<.05). CONCLUSION: Although clinical application of the specific functional shoe has shown clear positive effects on knee and ankle moments, the results of this study provide important background information regarding the kinematic mechanisms of these effects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1562-1569
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• 2018

Sensor readings always have a certain degree of randomness and fuzziness due to its intrinsic property, other electronic devices in the circuitry, wires and the rapidly changing environment. In an electrical control system, such readings will bring instability in the system and other undesired events especially if the signal hovers around the threshold. This paper proposes a Gaussian-based statistical approach in stabilizing the output through sampling the sensor data and automatic tuning the threshold to the range of multiple standard deviations. It takes advantage of the Central limit theorem and its properties assuming that a large number of sensor data samples will eventually converge to a Gaussian distribution. Experimental results demonstrate the effectiveness of the proposed algorithm in completely stabilizing the outputs over known filtering algorithms like Exponential smoothing and Kalman Filter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.12
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• pp.1124-1132
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• 2011

This paper deals with smooth path generation using B-spline for fixed-wing unmanned aerial vehicles manuevering in 2D environment. Hexagonal cell representation is employed to model the 2D environment, which features increased connectivity among cells over square cell representation. Subsequently, hexagonal cell representation enables smoother path generation based on a discrete sequence of path from the path planner. In addition, we present an on-line path smoothing algorithm incorporating B-spline path templates. The path templates are computed off-line by taking into account all possible path sequences within finite horizon. During on-line implementation, the B-spline curves from the templates are stitched together repeatedly to come up with a reference trajectory for UAVs. This method is an effective way of generating smooth path with reduced on-line computation requirement, hence it can be implemented on a small low-cost autopilot that has limited computational resources.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.185-192
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• 2006

By mistaking normal packets for harmful traffic, it may not offer service according to the intention of attacker with harmful traffic, because it is not easy to classify network traffic for normal service and it for DUoS(Distributed DoS) attack like the Internet worm. And in the IPv6 environment these researches on harmful traffic are weak. In this dissertation, hosts in the IPv6 environment are attacked by NETWIB and their attack traffic is monitored, then the statistical information of the traffic is obtained from MIB(Management Information Base) objects used in the IPv6. By adapting the ESM(Exponential Smoothing Method) to this information, a normal traffic boundary, i.e., a threshold is determined. Input traffic over the threshold is thought of as attack traffic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.348-354
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• 1993

In this research, a multi-tree coder at 9.6Kbits/sec using a novel scheme for adaptation of the short-term coefficients is developed. The overall delay of the tree coder is maintained at 2.5 msec(16 samples at the 6.4KHz sampling frequency). This coder produces good quality speech over ideal channels, and it is very robust to channel errors up to a bit error rate (BER) of $10^{-3}$. This robustness is achieved by using a parallel adaptation scheme in combination with the use of a smoothed version of the received excitation sequence for adaptation of the short-term prediction coefficients. For the multi-tree coder, reconstructed output speech is evaluated using signal-to-quantization noise ratios (SNR), segmental SNRs, and informal listening tests.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.117-124
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• 2009

If time series data with seasonal effect exist, various statistical models like winters for successful forecasts could be used. But if the data are not enough to estimate seasonal effect, not much methods are available. This paper proposes the statistical forecasting method based on cumulative data when the data are not enough to estimate seasonal effect. We apply this method to real cosmetic sales data and show its better performance over moving average method.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1216-1226
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• 2005

In this paper, a preventive transmission rate decision algorithm, called PTRD, is proposed for the transmission of live video over networks with dynamic bandwidth allocation capability. Frame analyzer predicts the bit-rates of future frames before encoding by analyzing the source information such as spatial variances and the degree of scene changes. By using the predicted bit-rates, transmission rate bounds are derived from the constraints of encoder and decoder buffers. To resolve the problem of renegotiation cost increment due to frequent renegotiations, the PTRD algorithm is presented to decide transmission rates considering the elapsed time after the recent renegotiation and the perceived video quality. From the simulation results, compared to the normalized LMS based method, PTRD is shown to achieve high channel utilization with low renegotiation cost and no delay violation.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.424-434
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• 2012

This paper presents a path planning algorithm of the unmanned aerial vehicle for the neutralization of the enemy firepower. The long range firepower of the ememy is usually located at the rear side of the mountain which is difficult to bomb. The path planner not only consider the differential constraints of the Unmanned Aerial Vehicle (UAV) but also consider the final approaching angle constraint. This problem is easily solved by incorporating the analytical upper bounded continuous curvature path smoothing algorithm into the Rapidly Exploring Random Tree (RRT) planner. The proposed algorithm can build a feasible path satisfying the kinematic constraints of the UAV on the fly. In addition, the curvatures of the path are continuous over the whole path. Simulation results show that the proposed algorithm can generate a feasible path of the UAV for the bombing mission regardless of the posture of the tunnel.