• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.42 no.5
• /
• pp.9-20
• /
• 2005

In this paper, we propose ubiTrack, a system which tracks users' location in indoor environments by employing infrared-based proximity method. Most of recently developed systems have focussed on performance and accuracy. For this reason, they adopted the idea of centralized management, which gathers all information in a main system to monitor users' location. However, these systems raise privacy concerns in ubiquitous computing environments where tons of sensors are seamlessly embedded into environments. In addition, centralized systems also need high computational power to support multiple users. The proposed ubiTrack is designed as a passive mobile architecture to relax privacy problems. Moreover, ubiTrack utilizes appropriate area as a unit to efficiently track users. To achieve this, ubiTrack overlaps each sensing area by utilizing the TDM (Time-Division Multiplexing) method. Additionally, ubiTrack exploits various filtering methods at each receiver and utilization module. The filtering methods minimize unexpected noise effect caused by external shock or intensity weakness of ID signal at the boundary of sensing area. ubiTrack can be applied not only to location-based applications but also to context-aware applications because of its associated module. This module is a part of middleware to support communication between heterogeneous applications or sensors in ubiquitous computing environments.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.607-612
• /
• 1986

최근 테니스의 저변인구가 크게 증가함에 따라 테니스 라켓의 제작기술도 상당한 수준에 이르렀고 설계제작의 자동화에 의해서 양질의 제품이 시판되고 있다. 그러나 라켓에 볼이 임팩트될때 생기는 진동으로 야기되는 테니스 엘보우 등, 해결해야 할 문제들이 아직도 남아 있다. 이와같이 테니스 라켓의 정적인 강도 뿐만아니라 동적인 특성도 중요한 관심의 대상이 되어감에 따라 볼 컨트롤을 용이하게 한다거나, 안정타점영역(Sweet Spot)의 확장과 그립부의 진동등에 의해서 발생하는 엘보우 현상을 방지하기 위해 여러가지 연구가 수행되어 왔다. 특히, 다차원 스펙트럼해석 및 모우드 해석법에의해 그립부에 미치는 진동원의 동정과 라켓의 동적거동에 대해서 연구되었고, 라켓의 재질변경과 그립부의 구조변경에 의한 안정타점영역에 영향을 미치는 모우드 파라미터(Modal Parameter)의 추정에 관한 연구도 수행되었다. 이러한 연구들은 결국 안정타점영역을 확장시키거나 테니스 엘보우를 방지하기 위한 것으로서 이러한 목적을 달성하기위해 테니스 라켓의 진동 모우드에 관계되는 파라미터들을 찾아서 그 모우드 파라미터의 변화에 따르느 진동 모우드의 거동에 대해서 연구할 필요가 있다. 본 논문에서는 실험적인 모우드 해석법을 실제 테니스 라켓에 적용하여 모우드 파라미터들을 구한 다음 그 파라미터의 변화에 따르는 안정타점영역의 변화를 컴퓨터 시뮬레이션을 통해서 예측하였다. 또한 안정타점영역을 넓히고 라켓의 동특성을 개선시킬 수 있는 모우드 파라미터를 찾아서 테니스 라켓의 설계, 제작 단계에 정보를 제공하는 CAD(Computer Aided Design)에 좋은 자료를 얻고자 한다. 있으나 파도에 의한 영향이 가장 크므로 본 논문에서는 파도에 의한 영향만을 고려하였다. 파도는 쌍동선에 외란으로 작용하며 측정할 수 없는 양이므로 PID, LQ 제어에서는 제어모델에 포함되지 않지만 LQG 제어에서는 제어모델에 포함된다. LQG 제어의 경우 제어모델에 파도를 백색잡음으로 가정하고 제어기를 구성한 것 (LQG1)과 2차의 쉐이핑필터(shaping filter)를 사용하여 구성한 것(LQG2)으로 나누었다.져 한다.) 식도 이물에 의한, 또는 식도경술에 의한 합병증이 초래한 경우는 식도점막열상 1례 (1.8 %), 식도 천공 1례 (1.8 %) 였으며, 기도이물에 의한, 또는 기관지경술에 의한 합병증이 초래한 경우는 무기폐 2례 (11.1 %), 폐렴 3례 (16.7 %)로 나타났다.5예에서 소실되었다. 5 ) 청각심리검사 (Psychoacoustic evaluation)에서 폴립은 술전에 Grade 1∼2의 사성이 있었던 11예중 술후 10예에서 Grade 0로 되었으며 Grade 1∼2의 사성이 있었던 3예의 결절에서도 모두 Grade 0로 정상화되었다.>치를 측정한 결과 투여전과 차이가 없었다. 7) 이상의 결과로 볼때 Cis-platinum 사용으로 인한 이중독증은 신장기능이 정상일때는 충분한 hydration으로써 예방이 가능하며 동시에 금기로 알려져왔던 감음성난청이 있는 두경부악성종양환자에서도 세심한 주의하에 적절히 사용한다면 좋은 결과를 얻을 수 있을 것으로 사려된다.은 결과를 얻었기에 문헌고찰과 함께 보고하는 바이다. 1) 이관폐쇄술후 18시간에 최초로 삼출액이 확인되었으며 그 이후는 전실험군에서 삼출성중이염이 유발되다. 2

• Journal of KIISE:Databases
• /
• v.41 no.4
• /
• pp.249-255
• /
• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.5
• /
• pp.444-450
• /
• 2015

The accuracy of small and low cost CCD camera is insufficient to provide data for precisely tracking unmanned aerial vehicles(UAVs). This study shows how UAV can hover on a human targeted tracking object by using CCD camera rather than imprecise GPS data. To realize this, UAVs need to recognize their attitude and position in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for an UAV to estimate of his attitude by environment recognition for UAV hovering, as one of the best important problems. In this paper, we describe a method for the attitude of an UAV using image information of a maker on the floor. This method combines the observed position from GPS sensors and the estimated attitude from the images captured by a fixed camera to estimate an UAV. Using the a priori known path of an UAV in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a marker on the floor and the estimated UAV's attitude. Since the equations are based on the estimated position, the measurement error may exist all the time. The proposed method utilizes the error between the observed and estimated image coordinates to localize the UAV. The Kalman filter scheme is applied for this method. its performance is verified by the image processing results and the experiment.

• KIPS Transactions on Software and Data Engineering
• /
• v.3 no.9
• /
• pp.361-368
• /
• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.7
• /
• pp.209-220
• /
• 2014

In this paper, we analyze the discriminability of features for the classification of transient signals with an ambient noise in a shallow water. For the classification of the transient signals, robust features for the variance of a noise are required due to a low SNR under a marine environment. In the modelling the ambient noise in shallow water, theoretical noise model, Wenz's observation data from the shallow water, and Yule-walker filter are used. Discrimination of each feature of the transient signals with an additive ambient noise is analyzed by utilizing a Fisher score. As the analysis of a classification accuracy about the transient signals of 24 classes using the selected features with a high discriminability, the features selected in the environment without a noise relatively have a good classification accuracy. From the analyzed results, we finally select a total 16 features out of 28 features. The recognition using the selected features results in the classification accuracy of 92% in SNR 20dB using Multi-class SVM.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.2
• /
• pp.27-34
• /
• 2001

Utterance verification is used in variable vocabulary word recognition to reject the word that does not belong to in-vocabulary word or does not belong to correctly recognized word. Utterance verification is an important technology to design a user-friendly speech recognition system. We propose a new utterance verification algorithm for no-training utterance verification system based on the minimum verification error. First, using PBW (Phonetically Balanced Words) DB (445 words), we create no-training anti-phoneme models which include many PLUs(Phoneme Like Units), so anti-phoneme models have the minimum verification error. Then, for OOV (Out-Of-Vocabulary) rejection, the phoneme-based confidence measure which uses the likelihood between phoneme model (null hypothesis) and anti-phoneme model (alternative hypothesis) is normalized by null hypothesis, so the phoneme-based confidence measure tends to be more robust to OOV rejection. And, the word-based confidence measure which uses the phoneme-based confidence measure has been shown to provide improved detection of near-misses in speech recognition as well as better discrimination between in-vocabularys and OOVs. Using our proposed anti-model and confidence measure, we achieve significant performance improvement; CA (Correctly Accept for In-Vocabulary) is about 89％, and CR (Correctly Reject for OOV) is about 90％, improving about 15-21％ in ERR (Error Reduction Rate).

• The KIPS Transactions:PartB
• /
• v.18B no.3
• /
• pp.147-156
• /
• 2011

This paper proposes a 3-stage (preprocessing, feature extraction, and classification) fault detection and classification algorithm for induction motors. In the first stage, a low-pass filter is used to remove noise components in the fault signal. In the second stage, a discrete cosine transform (DCT) and a statistical method are used to extract features of the fault signal. Finally, a back propagation neural network (BPNN) method is applied to classify the fault signal. To evaluate the performance of the proposed algorithm, we used one second long normal/abnormal vibration signals of an induction motor sampled at 8kHz. Experimental results showed that the proposed algorithm achieves about 100% accuracy in fault classification, and it provides 50% improved accuracy when compared to the existing fault detection algorithm using a cross-covariance method. In a real-world data acquisition environment, unnecessary noise components are usually included to the real signal. Thus, we conducted an additional simulation to evaluate how well the proposed algorithm classifies the fault signals in a circumstance where a white Gaussian noise is inserted into the fault signals. The simulation results showed that the proposed algorithm achieves over 98% accuracy in fault classification. Moreover, we developed a testbed system including a TI's DSP (digital signal processor) to implement and verify the functionality of the proposed algorithm.

• Journal of Broadcast Engineering
• /
• v.24 no.6
• /
• pp.919-927
• /
• 2019

In this paper, we propose an accurate camera calibration method for acquiring multiview stereoscopic images. Generally, camera calibration is performed by using checkerboard structured patterns. The checkerboard pattern simplifies feature point extraction process and utilizes previously recognized lattice structure, which results in the accurate estimation of relations between the point on 2-dimensional image and the point on 3-dimensional space. Since estimation accuracy of camera parameters is dependent on feature matching, accurate detection of checkerboard corner is crucial. Therefore, in this paper, we propose the method that performs accurate camera calibration method through accurate detection of checkerboard corners. Proposed method detects checkerboard corner candidates by utilizing 1-dimensional gaussian filters with succeeding corner refinement process to remove outliers from corner candidates and accurately detect checkerboard corners in sub-pixel unit. In order to verify the proposed method, we check reprojection errors and camera location estimation results to confirm camera intrinsic parameters and extrinsic parameters estimation accuracy.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_2
• /
• pp.1235-1243
• /
• 2021

Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.