• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.11-20
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• 2017

In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.4 s.316
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• pp.1-7
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• 2007

When the sensor geometry is poor, the user position estimate obtained by of GN (Gauss-Newton) method is often diverged in radio navigation. In other to avoid divergence problem QCLS (Quadratic Correction Least Square) method using TDOA (Time Difference of Arrival) measurements is introduced, but the estimation error is somewhat large. This paper presents the modified QCLS method using weighted least square. Since the weighting matrix is influenced by the unknown user position, two-step approach is employed in the proposed method. The weighting matrix is estimated in the first step using least square, and then find user position is obtained using weighted least square. Simulation results show that the performance of the proposed method is superior to the conventional QCLS all over the workspace.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.460-465
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• 2021

In active sonar, time delay estimation is used to find the distance between the target and the sonar. Among the time delay estimation methods for active sonar, estimation in the frequency domain is widely used. When estimating in the frequency domain, the time delay can be thought of as a frequency estimator, so it can be used relatively easily. However, this method is prone to rapid increase in error due to noise. In this paper, we propose a new method which applies weighted dictionary and sparsity in order to reduce this error increase and we extend it to two receivers to propose an algorithm for estimating the time delay between two receivers. And the case of applying the proposed method and the case of not applying the proposed method including the conventional frequency domain algorithm and Generalized Cross Correlation-Phase transform (GCC-PHAT) in a white noise environment were compared with one another. And we show that the newly proposed method has a performance gain of about 15 dB to about 60 dB compared to other algorithms.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.371-382
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• 2004

To improve the precision of relative positioning for GPS single frequency(L1) receiver, we accomplished the GPS data processing using the weighted smoothing techniques. The weighted phase smoothing technique is used to minimize the measurement error of pseudorange and position domain smoothing technique is adopted to make the complement of cycle-slip affection. we also considered some component errors like as ionospheric error, which are related with baseline length, and processed for several baselines (5, 10, 30, 40, and 150 km) to check the coverage area of this algorithm. This paper shows that weighted phase smoothing technique give more stable results after using this technique and the position domain smoothing technique can reduce the errors which are sensitive to the observational environment. Based on the results, we could find out that this algorithm is available for post-time and real-time applications and these techniques can be substitution methods which is able to get the high accuracy and precision without resolving the Integer ambiguity.

• Journal of the Korea Computer Graphics Society
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• v.24 no.4
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• pp.29-38
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• 2018

In this paper, we propose an automatic segmentation method of meniscus in knee MR images by automatic meniscus localization, multi-atlas-based locally-weighted voting, and patch-based edge feature classification. First, after segmenting the bone and knee articular cartilage, the volume of interest of the meniscus is automatically localized. Second, the meniscus is segmented by multi-atlas-based locally-weighted voting taking into account the weights of shape and intensity distribution in the volume of interest of the meniscus. Finally, to remove leakage to the collateral ligaments with similar intensity, meniscus is refined using patch-based edge feature classification considering shape and distance weights. Dice similarity coefficient between proposed method and manual segmentation were 80.13% of medial meniscus and 80.81 % for lateral meniscus, and showed better results of 7.25% for medial meniscus and 1.31% for lateral meniscus compared to the multi-atlas-based locally-weighted voting.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.409-414
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• 2007

The effect of multipath is especially serious in urban area and sea surface where buildings and water reflect GPS signal. Multipath brings about the performance degradation on many GPS application because the presence of multipath causes the diminution of pseudorange measurement accuracy in turn position accuracy. In this paper, a multipath mitigation named weighted correlation method is implemented on software GPS receiver, in which the asymmetric correlation function is compensated by modifying the late correlation value. Asymmetry compensation is obtained as weighted sum of two correlators which have different early-late chip spaces. This structure is adopted to lessen the computation load lower keeping up performance similar to that. The performance of implemented multipath mitigation technique is evaluated using GPS signal and multipath signal generated by GPS signal generator and software GPS receiver. The test results show that the weighted correlation method gives hefter performance than the standard correlator and the narrow correlator.

• Journal of KIISE:Information Networking
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• v.37 no.5
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• pp.409-414
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• 2010

The applications based on geographical location are increasing rapidly in wireless sensor networks (WSN). Recently, various localization algorithms have been proposed but the majority of algorithms rely on the specific hardware to measure the distance from the signal sources. In this paper, we propose the Weighted Multiple Rings Localization(WMRL). We assume that each deployed anchor node may periodically emit the successive beacon signals of the different power level. Then, the beacon signals form the concentric rings depending on their emitted power level, theoretically. The proposed algorithm defines the different weighting factor based on the ratio of each radius of ring. Also, If a sensor node may listen, it can find the innermost ring of the propagated signal for each anchor node. Based on this information, the location of a sensor node is derived by a weighted sum of coordinates of the surrounding anchor nodes. Our proposed algorithm is fully distributed and does not require any additional hardwares and the unreliable distance indications such as RSSI and LQI. Nevertheless, the simulation results show that the WMRL with two rings twice outperforms centroid algorithm. In the case of WMRL with three rings, the accuracy is approximately equal to WCL(Weighted Centroid Localization).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.113-118
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• 2012

In this paper, we propose the removal of search point using motion vector correlation and distance between reference frames in H.264/AVC. We remove the search points in full search method and predictive motion vectors in enhanced predictive zonal search method. Since the probability that the reference frame far from the current frame is selected as the best reference frame is decreased, we apply the weighted average based on distance between the current and reference frame to determine the fianl search range. In general, the size of search range is smaller than initial search range. We reduce motion estimation time using the final search range in full search method. Also, the refinement process is adaptively applied to each reference frame. The proposed methods reduce the computational throughput of full search method by 57.13% and of enhanced predictive zonal search by 14.71% without visible performance degradation.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.4
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• pp.83-90
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• 2018

Considering the increased threats from worldwide terrors and the increased demands on the blast resistant design of commercial buildings, this study is aimed at understanding the basic concept of blast resistant design and evaluating the blast performance with an actual design example. Although there are many differences between earthquake and blast loads, the design concept against both loads is similar in terms of allowing the plastic behavior of a structure and sharing the ductile detailing. Through the blast performance evaluation of a target building provided in this study, it is noted that a well-designed building for the conventional loads can have a certain level of blast resistance. However, this cannot be generalized since the blast load on a structure varies depending on the type of weapon, TNT equivalence, standoff distance, etc. Architectural planning with positioning the sacrificial structure or maintaining a sufficient standoff distance from the expected detonation is the simple and effective way of improving the blast resistance of a building.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.57-63
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• 1997

In this paper, we study the efficient feature vector extraction method and front-end processing to improve the performance of the speech recognition system using KT(Korea Telecommunication) database collected through various telephone channels. First of all, we compare the recognition performances of the feature vectors known to be robust to noise and environmental variation and verify the performance enhancement of the recognition system using weighted cepstral distance measure methods. The experiment result shows that the recognition rate is increasedby using both PLP(Perceptual Linear Prediction) and MFCC(Mel Frequency Cepstral Coefficient) in comparison with LPC cepstrum used in KT recognition system. In cepstral distance measure, the weighted cepstral distance measure functions such as RPS(Root Power Sums) and BPL(Band-Pass Lifter) help the recognition enhancement. The application of the spectral subtraction method decrease the recognition rate because of the effect of distortion. However, RASTA(RelAtive SpecTrAl) processing, CMS(Cepstral Mean Subtraction) and SBR(Signal Bias Removal) enhance the recognition performance. Especially, the CMS method is simple but shows high recognition enhancement. Finally, the performances of the modified methods for the real-time implementation of CMS are compared and the improved method is suggested to prevent the performance degradation.