• Title/Summary/Keyword: Mean vector

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A Study on the Local Climate in the Vicinity of Duckyang Bay , Korea (득량만일원의 국지기상 환경의 특성에 관한 연구)

  • 김유근
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.28 no.4
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    • pp.398-411
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    • 1992
  • The characteristics of local climate in the vicinity of Duckyang Bay have been investigated with the analysis of the surface observation data of Gohug District and the aerological data of Kwangju. In principal features of local climate, the annual range in temperature appeared identical with the mean value(24~$25^{\circ}C$) of the south coastal area, and evaporation from April to September was likely less than precipitation. The average speed of surface wind in Summer seemed higher than in other seasons on account of wea breeze. Relative humidity was 74%, annual average. In the mean cloud cover Summer(6.4) showed greater deal of amount than Winter(4.2). Duration of sunshine was the longest in May(268.4hrs), while the shortest in February(188.4hrs). The amount of the precipitable water was the greatest in July, whereas the least in January, and in Summer the greatest, in Autumn the second greatest, and in Spring the third greatest, and in Winter the least in consideration of seasonal orders. The Summer deviation was most remarkable around all sides. The direction of vector wind appeared the most changeable on the earth surface. At an altitude of 300mb all the winds blew west around all months. Moreover, water vapor transport was measured to be the greatest in Summer; while the least in Winter. So was the deviation of water vapor transport. And lastly frequency of occurrence of days in which a little cloud appeared(less than 5/10) was high except for Summer, when northerly winds blew; while frequency of occurrence of day plenty of clouds floated was outstandingly high at the time of strong southerly winds.

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Similar Question Search System for online Q&A for the Korean Language Based on Topic Classification (온라인가나다를 위한 주제 분류 기반 유사 질문 검색 시스템)

  • Mun, Jung-Min;Song, Yeong-Ho;Jin, Ji-Hwan;Lee, Hyun-Seob;Lee, Hyun Ah
    • Korean Journal of Cognitive Science
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    • v.26 no.3
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    • pp.263-278
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    • 2015
  • Online Q&A for the National Institute of the Korean Language provides expert's answers for questions about the Korean language, in which many similar questions are repeatedly posted like other Q&A boards. So, if a system automatically finds questions that are similar to a user's question, it can immediately provide users with recommendable answers to their question and prevent experts from wasting time to answer to similar questions repeatedly. In this paper, we set 5 classes of questions based on its topic which are frequently asked, and propose to classify questions to those classes. Our system searches similar questions by combining topic similarity, vector similarity and sequence similarity. Experiment shows that our method improves search correctness with topic classification. In experiment, Mean Reciprocal Rank(MRR) of our system is 0.756, and precision for the first result is 68.31% and precision for top five results is 87.32%.

Prediction of Combined Forced and Natural Turbulent Convection in a Vertical Plane Channel with an Elliptic-Blending Second Moment Closure (타원-혼합 2차모멘트 모형에 의한 강제와 자연대류가 복합된 수직 평판 난류유동의 예측)

  • Shin, Jong Keun;An, Jeong Soo;Choi, Young Don
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.29 no.11 s.242
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    • pp.1265-1276
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    • 2005
  • The elliptic conceptual second moment models for turbulent heat fluxes, which are proposed on the basis of elliptic-blending and elliptic-relaxation equations, are applied to calculate the combined forced and natural turbulent convection in a vertical plane channel. The models satisfy the near-wall balance between viscous diffusion, viscous dissipation and temperature-pressure gradient correlation, and also have the characteristics of approaching its respective conventional high Reynolds number model far away from the wall. Also the models are closely linked to the elliptic blending model which is used for the prediction of Reynolds stress. In order to calibrate the heat flux models, firstly, the distributions of mean temperature and scala flux in fully developed channel flow with constant wall difference temperature are solved by the present models. The buoyancy effect on the turbulent characteristics including the mean velocity and temperature, the Reynolds stress tensor, and the turbulent heat flux vector are examined. In the opposing flow, the turbulent transport is greatly enhanced with both the Reynolds stresses and the turbulent heat fluxes being remarkably increased; whereas, in the aiding flow, the opposite change is observed. The results of prediction are directly compared to the DNS to assess the performance of the model predictions and show that the behaviors of the turbulent heat transfer in the whole flow region are well captured by the present models.

Feasibility of Using Similar Electrocardiography Measured around the Ears to Develop a Personal Authentication System (귀 주변에서 측정한 유사 심전도 기반 개인 인증 시스템 개발 가능성)

  • Choi, Ga-Young;Park, Jong-Yoon;Kim, Da-Yeong;Kim, Yeonu;Lim, Ji-Heon;Hwang, Han-Jeong
    • Journal of Biomedical Engineering Research
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    • v.41 no.1
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    • pp.42-47
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    • 2020
  • A personal authentication system based on biosignals has received increasing attention due to its relatively high security as compared to traditional authentication systems based on a key and password. Electrocardiography (ECG) measured from the chest or wrist is one of the widely used biosignals to develop a personal authentication system. In this study, we investigated the feasibility of using similar ECG measured behind the ears to develop a personal authentication system. To this end, similar ECGs were measured from thirty subjects using a pair of three electrodes attached behind each of the ears during resting state during which the standard Lead-I ECG was also simultaneously measured from both wrists as baseline ECG. The three ECG components, Q, R, and S, were extracted for each subject as classification features, and authentication accuracy was estimated using support vector machine (SVM) based on a 5×5-fold cross-validation. The mean authentication accuracies of Lead I-ECG and similar ECG were 90.41 ± 8.26% and 81.15 ± 7.54%, respectively. Considering a chance level of 3.33% (=1/30), the mean authentication performance of similar ECG could demonstrate the feasibility of using similar ECG measured behind the ears on the development of a personal authentication system.

Channel Estimation Based on LMS Algorithm for MIMO-OFDM System (MIMO-OFDM을 위한 LMS 알고리즘 기반의 채널추정)

  • Hwang, Suk-Seung
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1455-1461
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    • 2012
  • MIMO-OFDM which is one of core techniques for the high-speed mobile communication system requires the efficient channel estimation method with low estimation error and computational complexity, for accurately receiving data. In this paper, we propose a channel estimation algorithm with low channel estimation error comparing with LS which is primarily employed to the MIMO-OFDM system, and with low computational complexity comparing with MMSE. The proposed algorithm estimates channel vectors based on the LMS adaptive algorithm in the time domain, and the estimated channel vector is sent to the detector after FFT. We also suggest a preamble architecture for the proposed MIMO-OFDM channel estimation algorithm. The computer simulation example is provided to illustrate the performance of the proposed algorithm.

Boundary Detection using Adaptive Bayesian Approach to Image Segmentation (적응적 베이즈 영상분할을 이용한 경계추출)

  • Kim Kee Tae;Choi Yoon Su;Kim Gi Hong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.22 no.3
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    • pp.303-309
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    • 2004
  • In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

Sparse Signal Recovery with Parallel Orthogonal Matching Pursuit and Its Performances (병렬OMP 기법을 통한 성긴신호 복원과 그 성능)

  • Park, Jeonghong;Jung, Bang Chul;Kim, Jong Min;Ban, Tae Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.8
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    • pp.1784-1789
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    • 2013
  • In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the orthogonal matching pursuit (OMP) which has been widely used as a greedy algorithm for sparse signal recovery. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the firest iteration, (2) the conventional OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP outperforms than the existing sparse signal recovery algorithms in terms of exact recovery ratio (ERR) for sparse pattern and mean-squared error (MSE) between the estimated signal and the original signal.

Target-Tracking System for Mobile Surveillance Robot Using CAMShift Image Processing Technique (CAMShift 영상 처리 기법을 이용한 기동형 경계 로봇의 목표추적 시스템)

  • Seo, Bong-Cheol;Kim, Sung-Soo;Lee, Dong-Youm
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.2
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    • pp.129-136
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    • 2014
  • Target-tracking systems are important for carrying out effective surveillance missions using mobile surveillance robots. In this paper, we propose a target-tracking algorithm using camera image data for a three-axis mobile surveillance robot and carry out an actual hardware test for verifying the proposed algorithm. The heading direction vector of a camera system is deduced from the position error between the viewfinder center and the object center in a camera image. The position error is obtained using the CAMShift(Continuously Adaptive Mean Shift) algorithm, an image processing technique. The performance test of an actual three-axis mobile surveillance robot was carried out for verifying the proposed target-tracking algorithm in a real environment.

Feature selection and prediction modeling of drug responsiveness in Pharmacogenomics (약물유전체학에서 약물반응 예측모형과 변수선택 방법)

  • Kim, Kyuhwan;Kim, Wonkuk
    • The Korean Journal of Applied Statistics
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    • v.34 no.2
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    • pp.153-166
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    • 2021
  • A main goal of pharmacogenomics studies is to predict individual's drug responsiveness based on high dimensional genetic variables. Due to a large number of variables, feature selection is required in order to reduce the number of variables. The selected features are used to construct a predictive model using machine learning algorithms. In the present study, we applied several hybrid feature selection methods such as combinations of logistic regression, ReliefF, TurF, random forest, and LASSO to a next generation sequencing data set of 400 epilepsy patients. We then applied the selected features to machine learning methods including random forest, gradient boosting, and support vector machine as well as a stacking ensemble method. Our results showed that the stacking model with a hybrid feature selection of random forest and ReliefF performs better than with other combinations of approaches. Based on a 5-fold cross validation partition, the mean test accuracy value of the best model was 0.727 and the mean test AUC value of the best model was 0.761. It also appeared that the stacking models outperform than single machine learning predictive models when using the same selected features.

Feature Extraction and Evaluation for Classification Models of Injurious Falls Based on Surface Electromyography

  • Lim, Kitaek;Choi, Woochol Joseph
    • Physical Therapy Korea
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    • v.28 no.2
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    • pp.123-131
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    • 2021
  • Background: Only 2% of falls in older adults result in serious injuries (i.e., hip fracture). Therefore, it is important to differentiate injurious versus non-injurious falls, which is critical to develop effective interventions for injury prevention. Objects: The purpose of this study was to a. extract the best features of surface electromyography (sEMG) for classification of injurious falls, and b. find a best model provided by data mining techniques using the extracted features. Methods: Twenty young adults self-initiated falls and landed sideways. Falling trials were consisted of three initial fall directions (forward, sideways, or backward) and three knee positions at the time of hip impact (the impacting-side knee contacted the other knee ("knee together") or the mat ("knee on mat"), or neither the other knee nor the mat was contacted by the impacting-side knee ("free knee"). Falls involved "backward initial fall direction" or "free knee" were defined as "injurious falls" as suggested from previous studies. Nine features were extracted from sEMG signals of four hip muscles during a fall, including integral of absolute value (IAV), Wilson amplitude (WAMP), zero crossing (ZC), number of turns (NT), mean of amplitude (MA), root mean square (RMS), average amplitude change (AAC), difference absolute standard deviation value (DASDV). The decision tree and support vector machine (SVM) were used to classify the injurious falls. Results: For the initial fall direction, accuracy of the best model (SVM with a DASDV) was 48%. For the knee position, accuracy of the best model (SVM with an AAC) was 49%. Furthermore, there was no model that has sensitivity and specificity of 80% or greater. Conclusion: Our results suggest that the classification model built upon the sEMG features of the four hip muscles are not effective to classify injurious falls. Future studies should consider other data mining techniques with different muscles.