• Title/Summary/Keyword: 통계적 테스트

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An analysis of correlation between EEG signal and HRV during attentional status with children under 15 years (15세 미만 아동을 대상으로 한 집중상태에서 EEG 신호와 HRV의 상관관계 분석)

  • Choi, Woo-Jin;Lee, Chug-Ki;Yoo, Sun-Kook
    • Science of Emotion and Sensibility
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    • v.14 no.2
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    • pp.269-278
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    • 2011
  • This paper illustrates the inter-relationship between the theta/alpha ratio of the EEG signal and multiple HRV related parameters associated with the cardiovascular system response during event-related stimuli. Both EEG and PPG signals were simultaneously recorded in 21 healthy subjects. All subjects had their attention focused on the CNT program for nine minutes. Time-frequency analysis was applied to the EEG and PPG signals. The theta/alpha ratio was extracted from the EEG results, and the HRV features, including beat interval(1), SDNN(2), RMSSD(3), NN50(4), LF(5), HF(6), and LFIHF(7), were extracted from the PPG. Through multiple linear regression, the relationship ($R^2$) between the multiple combined features and the theta/alpha rhythm was identified. As a result, the combinations of $R^2$($R^2=0.253$; seven dimensions) and the theta/alpha ratio indicated a higher inter-relationship value than those of other combinations. The combinations of features that were greater than three dimensions, based on {SDNN(2), HF(6)}, generally showed higher $R^2$ value. We demonstrate that the high dimensional combinations had a higher correlation than did the low dimensional combinations.

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Design and Development of Middleware for Clinical Trial System based on Brain MR Image (뇌 MR 영상기반 임상연구 시스템을 위한 미들웨어 설계 및 개발)

  • Jeon, Woong-Gi;Park, Kyoung-Jong;Lee, Young-Seung;Choi, Hyun-Ju;Jeong, Sang-Wook;Kim, Dong-Eog;Choi, Heung-Kook
    • Journal of Korea Multimedia Society
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    • v.15 no.6
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    • pp.805-813
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    • 2012
  • In this paper, we have designed and developed a middleware for an effectively approaching database to the existed brain disease clinical research system. The brain disease clinical research system was consisted of two parts i.e., a register and an analyzer. Since the register collects the registration data the analyzer yields a statistical data which based on the diverse variables. The middleware has designed to database management and a large data query processing of clients. By separating the function of each feature as a module, the module which was weakened connectivity between functionalities has been implemented the re-use module. And image data module used a new compression method from image to text for an effective management and storage in database. We tested the middleware system using 700 actual clinical medical data. As a result, the total data transmission time was improved maximum 115 times faster than the existing one. Through the improved module structures, it is possible to provide a robust and reliable system operation and enhanced security functionality. In the future, these middleware importances should be increased to the large medical database constructions.

Invariant Classification and Detection for Cloth Searching (의류 검색용 회전 및 스케일 불변 이미지 분류 및 검색 기술)

  • Hwang, Inseong;Cho, Beobkeun;Jeon, Seungwoo;Choe, Yunsik
    • Journal of Broadcast Engineering
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    • v.19 no.3
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    • pp.396-404
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    • 2014
  • The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.

Design and Analysis of Pseudorandom Number Generators Based on Programmable Maximum Length CA (프로그램 가능 최대길이 CA기반 의사난수열 생성기의 설계와 분석)

  • Choi, Un-Sook;Cho, Sung-Jin;Kim, Han-Doo;Kang, Sung-Won
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.2
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    • pp.319-326
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    • 2020
  • PRNGs(Pseudorandom number generators) are essential for generating encryption keys for to secure online communication. A bitstream generated by the PRNG must be generated at high speed to encrypt the big data effectively in a symmetric key cryptosystem and should ensure the randomness of the level to pass through the several statistical tests. CA(Cellular Automata) based PRNGs are known to be easy to implement in hardware and to have better randomness than LFSR based PRNGs. In this paper, we design PRNGs based on PMLCA(Programable Maximum Length CA) that can generate effective key sequences in symmetric key cryptosystem. The proposed PRNGs generate bit streams through nonlinear control method. First, we design a PRNG based on an (m,n)-cell PMLCA ℙ with a single complement vector that produces linear sequences with the long period and analyze the period and the generating polynomial of ℙ. Next, we design an (m,n)-cell PC-MLCA based PRNG with two complement vectors that have the same period as ℙ and generate nonlinear sequences, and analyze the location of outputting the nonlinear sequence.

The Development Device of the Local Food Industry - Focusing on Local Food CEOs in Daejeon.Chungnam Province - (향토음식 산업의 발전 방안 - 대전.충청지역 향토음식경영주를 중심으로 -)

  • Kim, Keun-Jong
    • Culinary science and hospitality research
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    • v.16 no.1
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    • pp.78-91
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    • 2010
  • This study aims to find a way of developing the local food industry by examining CEOs who run local food restaurants. As a result of researching the local food of Daejeon and the Chungnam province, there were 106 kinds of local food. However, all the CEOs of local food restaurants were having difficulty in operating. In order to survey the local food restaurants for development devices, 450 copies of the questionnaire were distributed to man- or woman-CEOs who operate a local food restaurant in Daejeon city and the Chungnam province. Among 450 copies of the distributed questionnaire, 390 copies were collected for this study. It used a total of 370 copies as the effective samples for an empirical analysis except 20 copies with false entries among them. The result of the empirical analysis showed as follows: 1) For the recognition of the local food, there was not difference between males and females. 2) For the factor of success on the local food restaurants, both males and females answered food taste was most important. 3) For the reason why chain business of the local food restaurants was difficult, both males and females answered there were too many side dishes coming with a main dish. 4) For the way of reinforcing competitive power of the local food restaurants, most of the male respondents and all females thought there should be financial support.

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Compromised feature normalization method for deep neural network based speech recognition (심층신경망 기반의 음성인식을 위한 절충된 특징 정규화 방식)

  • Kim, Min Sik;Kim, Hyung Soon
    • Phonetics and Speech Sciences
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    • v.12 no.3
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    • pp.65-71
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    • 2020
  • Feature normalization is a method to reduce the effect of environmental mismatch between the training and test conditions through the normalization of statistical characteristics of acoustic feature parameters. It demonstrates excellent performance improvement in the traditional Gaussian mixture model-hidden Markov model (GMM-HMM)-based speech recognition system. However, in a deep neural network (DNN)-based speech recognition system, minimizing the effects of environmental mismatch does not necessarily lead to the best performance improvement. In this paper, we attribute the cause of this phenomenon to information loss due to excessive feature normalization. We investigate whether there is a feature normalization method that maximizes the speech recognition performance by properly reducing the impact of environmental mismatch, while preserving useful information for training acoustic models. To this end, we introduce the mean and exponentiated variance normalization (MEVN), which is a compromise between the mean normalization (MN) and the mean and variance normalization (MVN), and compare the performance of DNN-based speech recognition system in noisy and reverberant environments according to the degree of variance normalization. Experimental results reveal that a slight performance improvement is obtained with the MEVN over the MN and the MVN, depending on the degree of variance normalization.

A comparative study of the improvement after different self-assessment methods of tooth preparation (치아 삭제의 다른 자가 평가 방법 후 개선에 대한 비교 연구)

  • Kim, JungHan;Son, Keunbada;Lee, Kyu-Bok
    • Journal of Dental Rehabilitation and Applied Science
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    • v.35 no.4
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    • pp.220-227
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    • 2019
  • Purpose: The purpose of this study was to compare the degree of tooth preparation abilities of students according to three self-assessment methods. Materials and Methods: forty-eight sophomores in Kyungpook National University College of Dentistry were divided into three experimental groups. Students performed tooth preparation of the left mandibular first molar for full gold crown. They performed self-assessment using the three methods (visual, digital, and putty index self-assessment group), and reperformed tooth preparation. An intraoral scanner was used to scan each tooth model (prepared tooth and unprepared tooth), and data were acquired in standard tessellation language (STL) file format. The STL files of prepared tooth and unprepared tooth were superimposed using the 3-dimensional analysis software (Geomagic control X). And the reduction amount was measured. In the statistical analysis, all values of reduction amount were analyzed with the Wilcoxon signed rank test and Kruskal-Wallis test (α = 0.05). Results: The three self-assessment methods showed statistically significant differences (P < 0.001). The putty index self-assessment group showed the highest reduction in error than the digital self-assessment method. Conclusion: Within limitations of this study, students showed significant differences in improvement of tooth preparation ability according to the three self-evaluation methods.

Evaluation of physical properties of polycarbonate temporary restoration materials (폴리카보네이트 임시수복재료의 물성 평가)

  • Kim, Gwang-Yun;Kwak, Young-Hun;Kim, Hee-Jung
    • Journal of Dental Rehabilitation and Applied Science
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    • v.36 no.3
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    • pp.168-175
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    • 2020
  • Purpose: The purpose is to test and evaluate the physical properties of commonly used temporary restoration materials and newly emerged materials. Materials and Methods: Four groups of polymer materials were evaluated: Polymethyl methacrylate (PMMA) 2 groups, Polyetheretherketone (PEEK), Polycarbonate. Four physical properties were tested: surface hardness, bending strength, abrasion resistance during wear, wear behavior. The 3-axis bending strength and Vickers hardness test were measured using a universal testing machines respectively. The microstructure was observed with a scanning electron microscope and weight comparison was evaluated after 100,000 chewing tests using a chewing simulator. Kruskal wallis test was performed to evaluate statistical significance. Results: The four groups showed the highest flexural strength and Vickers hardness of PEEK, followed by PC, PMMA-H, PMMA-T. Microstructure observation also showed the least surface roughness in the PEEK group, followed by PC, PMMA-H, PMMA-T. Conclusion: PC is considered to have sufficient mechanical properties that can be applied to the manufacture of temporary teeth. However, further studies, such as biocompatibility, are considered to be necessary for practical clinical applications.

Markov Chain Properties of Sea Surface Temperature Anomalies at the Southeastern Coast of Korea (한국 남동연안 이상수온의 마르코프 연쇄 성질)

  • Kang, Yong-Q.;Gong, Yeong
    • 한국해양학회지
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    • v.22 no.2
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    • pp.57-62
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    • 1987
  • The Markov chain properties of the sea surface temperature (SST) anomalies, namely, the dependency of the monthly SST anomaly on that of the previous month, are studied based on the SST data for 28years(1957-1984) at 5 stations in the southeastern coast of Korea. Wi classified the monthly SST anomalies at each station into the low, the normal and the high state, and computed transition probabilities between SST anomalies of two successive months The standard deviation of SST anomalies at each station is used as a reference for the classification of SST anomalies into 3states. The transition probability of the normal state to remain in the same state is about 0.8. The transition probability of the high or the low states to remain in the same state is about one half. The SST anomalies have almost no probability to transit from the high (the low) state to the low (the high) state. Statistical tests show that the Markov chain properties of SST anomalies are stationary in tine and homogeneous in space. The multi-step Markov chain analysis shows that the 'memory' of the SST anomalies at the coastal stations remains about 3 months.

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A New Look at the Statistical Method for Remote Sensing of Daily Maximum Air Temperature (위성자료를 이용한 일최고온도 산출의 통계적 접근에 관한 고찰)

  • 변민정;한경수;김영섭
    • Korean Journal of Remote Sensing
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    • v.20 no.2
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    • pp.65-76
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    • 2004
  • This study aims to estimate daily maximum air temperature estimated using satellite-derived surface temperature and Elevation Derivative Database (EDD). The analysis is focused on the establishment of a semi-empirical estimation technique of daily maximum air temperature through the multiple regression analysis. This tests the contribution of EDD in the air temperature estimation when it is added into regression model as an independent variable. The better correlation is shown with the EDD data as compared with the correlation without this data set. In order to provide a progressive estimation technique, we propose and compare three approaches: 1) seasonal estimation non-considering landcover, 2) seasonal estimation considering landcover, and 3) estimation according to landcover type and non-considering season. The last method shows the best fit with the root-mean-square error between 0.56$^{\circ}C$ and 3.14$^{\circ}C$. A cross-validation procedure is performed for third method to valid the estimated values for two major landcover types (cropland and forest). For both landcover types, the validation results show reasonable agreement with estimation results. Therefore it is considered that the estimation technique proposed may be applicable to most parts of South Korea.