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

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.2
• /
• pp.55-65
• /
• 2011

In this paper, a novel method of marker detection robust against marker occlusion in augmented reality is proposed. the proposed method consists of four steps. In the first step, in order to effectively detect an occluded marker, we first utilize the Affine-SIFT (ASIFT, Affine-Scale Invariant Features Transform) for detecting matching points between an enrolled marker and an input images with an occluded marker. In the second step, we apply the Principal Component Analysis (PCA) for eliminating outlier of the matching points in the enrolled marker. And then matching points are projected to the first and second axis for longest value and the shortest value of an ellipse are determined by average distance between the projected points and a center of the points. In the third step, Convex-hull vertices including matching points are considered as polygon vertices for estimating a geometric affine transformation. In the final step, by estimating the geometric affine transformation of the points, a marker robust against a marker occlusion is detected. Experimental results have shown that the proposed method effectively detects occlude markers.

• Journal of Astronomy and Space Sciences
• /
• v.22 no.3
• /
• pp.283-292
• /
• 2005

Ionosphere is deeply coupled to the space environment and introduces the perturbations to radio signal because of its electromagnetic characteristics. Therefore, the status of ionosphere can be estimated by analyzing the GPS signal errors which are penetrating the ionosphere and it can be the key to understand the global circulation and change in the upper atmosphere, and the characteristics of space weather. We used 9 GPS Continuously Operating Reference Stations (CORS), which have been operated by Korea Astronomy and Space Science Institute (KASI) , to determine the high precision of Total Electron Content (TEC) and the pseudorange data which is phase-leveled by a linear combination with carrier phase to reduce the inherent noise. We developed the method to model a regional ionosphere with grid form and its results over South Korea with $0.25^{\circ}\;by\;0.25^{\circ}$ spatial resolution. To improve the precision of ionosphere's TEC value, we applied IDW (Inverse Distance Weight) and Kalman Filtering method. The regional ionospheric model developed by this research was compared with GIMs (Global Ionosphere Maps) preduced by Ionosphere Working Group for 8 days and the results show $3\~4$ TECU difference in RMS values.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.2
• /
• pp.120-130
• /
• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.1
• /
• pp.32-43
• /
• 2020

The transfer time is an important factor in establishing public transportation planning and policy. Therefore, in this study, the influencing factors of the transfer time for transit users were identified using smart card data, and the estimation results for the transfer time using the deep learning method such as deep neural network models were compared with traditional regression models. First, the intervals and the distance to the bus stop had positive effects on the subway-to-bus transfer time, and the number of bus routes had a negative effect. This also showed that the transfer time is affected by the area in which the subway station exists. Based on the influencing factors of the transfer time, the deep learning models were developed and their estimation results were compared with the regression model. For model performance, the deep learning models were better than those of the regression models. These results can be used as basic data for transfer policies such as the differential application of transit allowance times according to region.

• Journal of Korean Society for Geospatial Information Science
• /
• v.23 no.4
• /
• pp.43-48
• /
• 2015

We studied on pseudo-range correction(PRC) modeling in order to improve differential GNSS(DGNSS) accuracy. The PRC is the range correction information that provides improved location accuracy using DGNSS technique. The digital correction signal is typically broadcast over ground-based transmitters. Sometimes the degradation of the positioning accuracy caused by the loss of PRC signals, radio interference, etc. To prevent the degradation, in this paper, we have designed a PRC model through polynomial curve fitting and evaluated this model. We compared two quantities, estimations of PRC using model parameters and observations from the reference station. In the case of GPS, the average is 0.1m and RMSE is 1.3m. Most of GPS satellites have a bias error of less than ${\pm}1.0m$ and a RMSE within 3.0m. In the case of GLONASS, the average and the RMSE are 0.2m and 2.6m, respectively. Most of satellites have less than ${\pm}2.0m$ for a bias error and less than 3.0m for RMSE. These results show that the estimated value calculated by the model can be used effectively to maintain the accuracy of the user's location. However;it is needed for further work relating to the big difference between the two values at low elevation.

• Journal of Korean Society of Transportation
• /
• v.30 no.1
• /
• pp.19-30
• /
• 2012

The majority of daily travel demands concentrate at particular time-periods, which causes the difficulties in the travel demand analysis and the corresponding benefit estimation. Thus, it is necessary to consider time-specific traffic characteristics to yield more reliable results. Traditionally, na$\ddot{i}$ve, heuristic, and statistical approaches have been applied to address the peak-hour ratio. In this study, a hybrid clustering model which is one of the statistical methods is applied to calculate the peak-hour ratio and its duration. The 2009 national 24-hour traffic data provided by the Korea institute of Construction Technology are used. The analysis is conducted dividing vehicle types into passenger cars and trucks. For the verification for the usefulness of the methodology, the toll collection system data by the Korea Express Corporation are collected. The result of the research shows lower errors during the off-peak hours and night times and increasing error ratios as the travel distance increases. Since the method proposed can reduce the arbitrariness of analysts and can accommodate the statistical significance test, the model could be considered as a more robust and stable methodology. It is hoped that the result of this paper could contribute to the enhancement of the reliability for the travel demand analysis.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
• /
• 2001.11a
• /
• pp.54-54
• /
• 2001

지필의 수축 현상은 섬유의 특성, Forming 공정에서 섬유배향Drying, 온도조건, Size P Press Y- Coating 공정 에서 Rewetting, 공정 중의 Tension, Draw등에 의 해 영 향을 받게 된다. 특히 Drying 공정에서는 지필 수분이 증발하면서 섬유의 자체 수축 및 섬유결합 부의 Micro compression이 발생하게 된다. 그리고 Draw, Canvas Tension, Cylinder 온도둥과 같은 공정 조건의 변동에 따라 지필 수축률의 차이가 발생하며 제품의 M MD/CD의 강도적 특성 및 칫수안정성 컬등의 품질과 상관성을 갖는다. 일반적으로 제 품의 신축률을 측정하는 일반적인 방법은 Reel 샘플을 일정시간 침수하여 종이 내부의 응력을 제거한 후 전후의 치수 차이를 비교하는 것이다. 그러나 이 방법을 통해서는 실 질적으로 Dryer 내부의 어느 단계에서 어느 정도의 수축이 발생하는지를 판단할 수는 없다. 본 연구는 Dryer에서 Reel 까지의 종이 수축 변화를 On - Line상에서 직접 측정한 적 용 사례와 공정 조건에 따른 지필 수축의 변화를 측정한 결과에 대한 것이다. 여기서 사용된 On-Line 지필 수축기는 직진성의 레이저를 이동식 지지대에 설치하여 전/후측 의 지필과 Cy linder 양끝의 거리 차이를 측정하여 지필의 폭을 계산할 수 있도록 자체 개발하였다. 이 설비를 이용하여 Dryer 내부에서 지필 수축이 급격이 일어나는 C Cylinder 군을 찾아 스팀압력과 Bel Run의 진공도, Canvas Tension, Draw 공정조건을 조정하였고 결과적으로 제품의 신축률 개선 효과를 가져올 수 있었다. 본 연구에서 개발한 On-Line 지필 수축 측정 기법은 종이 칫수 안정성과 관련하여 향후 공정 최적화 작업의 진단 도구로서 적극적으로 활용할 수 있을 것으로 기대된다.었다. 특히 지분의 경우, 참여한 회사의 지분관련 complain이 약 80% 정도 감소하는 결과를 나타 내었다. 또한 백상지의 경우 ink jet 프린터에 많이 사용됨으로 ink jet 프린터의 인쇄 적성을 image analyzer로 측정한 결과 산화전분 보다 향상된 결과를 나타내었다. 있다 고 사료되었다.칼비터에 의한 고해나 큰 물성적으로 큰 차이를 보이지는 않고 있 었다. 단지 섬유의 차이가 고해방식의 차이보다 월등히 크다는 사실을 보이고 있다 이러한 점은 섬유장의 길이에서도 볼 수 있다. 칼비터가 섬유를 절단하기만 하고 닥방망이 고해가 섬유장의 변화를 일으키지 않는다면 틀림없이 평균 섬유장의 차이가 생길것이다.의 여수도가 7 70% 이상 개선되는 것으로 나타났다.측정하였다. 또한 카르복실기 정량과 종이의 pH 측정 및 X -ray Diffractometer를 이용하여 결정화도를 측정하였다. 본 연구의 결과, 시간의 경과에 따라서 탄소의 결합에너지는 분포가 C-H에서 COO-, 또는 C=O로 달라짐으로써 종 이가 산화되고 있다는 것을 알 수 있었다. 또한 이 결합에너지 분포의 변화가 펄프의 종류 에 따라서 다르게 이동함으로써 제조된 시트의 표면 산화반응이 서로 다르게 일어나고 있음 을 알 수 있었으며, 이는 사용한 펄프의 화학 조성분의 차이에 기인한 것이라 사료된다.>NW 단열군이 연구지역 내에서 지하수 유동성이 가장 높은 단열군으로 추정된다. 이러한 사실은 3개 시추공을 대상으로 실시한 시추공 내 물리검층과 정압주입시험에서도 확인된다.. It was resulted from increase of weight of single cocoon. "Manta"2.5ppm produced 22.2kg of cocoon. It is equal to 9% increase in index, as compared to that of control.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.18 no.5
• /
• pp.488-495
• /
• 2012

The real-time indoor location technology using radio waves has been studied in a variety of environments. One of them, a ship which consists of steel structure has high reception rate but causes significant ranging error due to the reflection of radio waves. In order to reduce location measurement errors that occurs in such a environment, this paper, based on CSS of IEEE 802.15.4a, presents compensation algorithm for localization using modified bilateration and pyroelectric sensor in a ship. The proposed system reduces the number of fixed nodes by estimating the appropriate reception distance between mobile node and fixed node through the analysis of CSS characteristic in a narrow passage such as ship corridors. Also, in the corner section which the ranging errors are significantly fluctuated due to the reflection and diffraction of radio waves, we recognize the location by tracking the a moving section using modified bilateration technique and pyroelectric sensor. The experimental results show that the location accuracy and efficiency of the proposed algorithm are improved 86.2 % compared to general method.

• Journal of IKEEE
• /
• v.24 no.2
• /
• pp.638-648
• /
• 2020

Currently, the method of user-follwoing in intelligent cooperative robots usually based in vision system and using Lidar is common and have excellent performance. But in the closed space of Corona 19, which spread worldwide in 2020, robots for cooperation with medical staff were insignificant. This is because Medical staff are all wearing protective clothing to prevent virus infection, which is not easy to apply with existing research techniques. Therefore, in order to solve these problems in this paper, the ultrasonic sensor is separated from the transmitting and receiving parts, and based on this, this paper propose that estimating the user's position and can actively follow and cooperate with people. However, the ultrasonic sensors were partially applied by improving the Median filter in order to reduce the error caused by the short circuit in communication between hard reflection and the number of light reflections, and the operation technology was improved by applying the curvature trajectory for smooth operation in a small area. Median filter reduced the error of degree and distance by 70%, vehicle running stability was verified through the training course such as 'S' and '8' in the result.