• 디지털산업정보학회논문지
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• 제13권4호
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• pp.231-245
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• 2017

The purpose of this study is to analyze the trend line through scatter diagram analysis on correlation between SNS addiction tendencies and learning attitudes, figure out the knee point influencing learning attitudes negatively in detail, and examine influence among subareas. To address the goal, study questions are formulated as follows. First, this author did screening on the data of variables measured and analyzed descriptive statistics. Second, this researcher produced the trend line by drawing a scatter diagram in order to analyze correlation between SNS addiction tendencies, withdrawal symptoms, excessive communication, and excessive time wasting, and learning attitudes exploratorily. Third, to explore correlation between self-evaluation, learning participation, and developmental attitudes, the subfactors of learning attitudes related to SNS addiction tendencies, this author drew a scatter diagram and analyzed the threshold of positive and negative correlation. To verify the study questions, the SNS addiction tendency scale and learning attitude scale were applied to 301 university students in Chungcheong area. According to the study results, first, their learning attitudes are influenced by SNS addiction tendencies, excessive communication and excessive time wasting, and they are not influenced by withdrawal symptoms that much. Second, excessive communication, a factor of SNS addiction tendencies, and self-evaluation and developmental attitudes, factors of learning attitudes, show positive correlation to some extent and indicate negative correlation after the threshold. However, excessive communication and learning participation are found to show no correlation. Third, according to the results of examining correlation with learning attitudes by dividing them into excessive communication and excessive time wasting groups with the knee point of 1.40, as the symptom of excessive communication is found more, it influences self-evaluation, learning participation, developmental attitudes, and learning attitudes more negatively in general. The result of this study is expected to provide foundational material necessary to develop educational programs to prevent undergraduates' excessive SNS use and SNS addiction which can be used in the scenes of counseling or education.

• 제어로봇시스템학회논문지
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• 제3권5호
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• pp.511-519
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• 1997

This paper presents the automatic recognition algorithm of the license number in on vehicle image. The proposed algorithm uses the correlation coefficient and Hough transform to detect license plate. The m/n ratio reduction is performed to save time and memory. By the correlation coefficient between the standard pattern and the target pattern, licence plate area is roughly extracted. On the extracted local area, preprocessing and binarization is performed. The Hough transform is applied to find the extract outline of the plate. If the detection fails, a smaller or a larger standard pattern is used to compute the correlation coefficient. Through this process, the license plate of different size can be extracted. Two algorithms to each separate number are proposed. One segments each number with projection-histogram, and the other segments each number with the label. After each character is separated, it is recognized by the neural network. This research overlomes the problems in conventional methods, such as the time requirement or failure in extraction of outlines which are due to the processing of the entire image, and by processing in real time, the practical application is possible.

• Journal of the Korean Data and Information Science Society
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• 제24권3호
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• pp.651-658
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• 2013

For the marginal model and generalized estimating equations (GEE) method there is important full covariates conditional mean (FCCM) assumption which is pointed out by Pepe and Anderson (1994). With longitudinal data with time-varying stochastic covariates, this assumption may not necessarily hold. If this assumption is violated, the biased estimates of regression coefficients may result. But if a diagonal working correlation matrix is used, irrespective of whether the assumption is violated, the resulting estimates are (nearly) unbiased (Pan et al., 2000).The quadratic inference functions (QIF) method proposed by Qu et al. (2000) is the method based on generalized method of moment (GMM) using GEE. The QIF yields a substantial improvement in efficiency for the estimator of ${\beta}$ when the working correlation is misspecified, and equal efficiency to the GEE when the working correlation is correct (Qu et al., 2000).In this paper, we interest in whether the QIF can improve the results of the GEE method in the case of FCCM is violated. We show that the QIF with exchangeable and AR(1) working correlation matrix cannot be consistent and asymptotically normal in this case. Also it may not be efficient than GEE with independence working correlation. Our simulation studies verify the result.

• 대한안전경영과학회지
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• 제13권4호
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• pp.273-282
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• 2011

Nowadays, our industries and occupation are increased under the economy development of government. So, this paper introduce to compare with coefficient's of correlation on the time series of the education and the qualification in our country. For this reason, the decision making to qualifications' foresight which will be change to the education category-prospective on the time series. The qualification has claasified 5 degrees-master craftsman, professional engineer, engineer, technician(or industrial engineer), craftsman - and 516 qualification items. Education has classified to 4 degrees(7 degrees) - elementary, middle, high, high scholastic level school(college, university, graduation). This paper has matched to educational classification and qualification classification through the following method. We defined the same level between education and qualification after analysed correlation under the time series, so the craftsman equals high school graduation people, technician equals college graduation people, engineer quals university graduation people, now we could not analyse master and professional levels. This paper will suggest to the qualification's future policy direction and improve the education policy direction.

• 전자공학회논문지D
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• 제35D권3호
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• pp.63-69
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• 1998

In this paper, a new input method is proposed to improve shift-invariant property of a photorefractive correlator andwe implemented real-time optical pattern recognition system using it. In the conventional photorefractive correlator, it is vrey difficult to satisfy the Bragg condition in the pattern recognition process. So, correlation peak is decreased heavily for the shift of input image. If a liquid crystal television(LCTV) without an anlyzer is used as input device, we can get the correlation result regardless of shift of input image because beam path is not changed during storage of holographic filter and correlation process. Also recording time of a holographic matched filter in photorefractive crystal is reduced and the correlation peak is increased because incident beam on the LCTV is transmitted completely. Therefore total optical efficiency is improved. We compared and analyzed the correlation results of proposed photorefractive correlator by computer simulation and optical experiment. We used a BaTiO$_{3}$ single crystal which has high diffraction efficiency in optical experiment.

• 한국음향학회지
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• 제43권4호
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• pp.406-413
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• 2024

본 논문은 임펄스성 잡음에 견실한 시간 지연을 추정 방법을 제안한다. 제안하는 방법은 Generalized Cross Correlation - Phase Transform(GCC-PHAT) 방법에 비선형 전처리와 주파수 영역 저역 통과 필터를 사용한다. 본 논문에서는 GCC-PHAT의 연산 과정을 DFT로 다시 해석함으로써 GCC-PHAT에서 시간 지연 추정에 실제 사용되는 유효한 주파수 대역이 있음을 파악하고, 저역 통과 필터 사용하여 유효 대역만을 사용하면 잡음 성분을 줄여서 시간 추정 성능을 향상시킬 수 있음을 보인다. 제안한 방법을 임펄스성 잡음 환경에서 전통적인 GCC-PHAT와 비교함으로써 추정 견실성이 향상됨을 보인다.

• 대기
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• 제26권4호
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• pp.649-663
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• 2016

This study investigates eddy transports in terms of space and time for momentum, heat, and moisture, emphasizing comparison of the results in three reanalysis data sets including ERA-Interim from the European Center for Medium-range Weather Forecasts (ECMWF), NCEP2 from the National Center for Environmental Prediction and the Department of Energy (NCEP-DOE), and JRA-55 from the Japan Meteorological Agency (JMA) during boreal winter. The magnitudes for eddy transports of momentum in ERA-Interim are represented as the strongest value in comparison of three data sets, which may be mainly come from that both zonal averaged meridional and zonal wind tend to follow the hierarchy of ERA-Interim, NCEP2, and JRA-55. Whereas in relation to heat and moisture eddy transports, those of NCEP2 are the strongest, implying that zonal averaged air temperature (specific humidity) tend to follow the raking of NCEP2, ERA-Interim, and JRA-55 (NCEP2, JRA-55, and ERA-Interim), except that transient eddy transports for heat in ERA-Interim are the strongest involving both meridional wind and air temperature. The stationary and transient eddy transports in the context of space and time correlation, and intensity of standard deviation demonstrate that the correlation (intensity of standard deviation) influence the structure (magnitude) of eddy transports. The similarity between ERA-Interim and NCEP2 (ERA-Interim and JRA-55) of space correlation (time correlation) closely resembles among three data sets. A resemblance among reanalysis data sets of space correlation is larger than that of time correlation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권10호
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• pp.3475-3489
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• 2014

Here we present a simple flame detection method for an infrared (IR) thermal camera based real-time fire surveillance digital signal processor (DSP) system. Infrared thermal cameras are especially advantageous for unattended fire surveillance. All-weather monitoring is possible, regardless of illumination and climate conditions, and the data quantity to be processed is one-third that of color videos. Conventional IR camera-based fire detection methods used mainly pixel-based temporal correlation functions. In the temporal correlation function-based methods, temporal changes in pixel intensity generated by the irregular motion and spreading of the flame pixels are measured using correlation functions. The correlation values of non-flame regions are uniform, but the flame regions have irregular temporal correlation values. To satisfy the requirement of early detection, all fire detection techniques should be practically applied within a very short period of time. The conventional pixel-based correlation function is computationally intensive. In this paper, we propose an IR camera-based simple flame detection algorithm optimized with a compact embedded DSP system to achieve early detection. To reduce the computational load, block-based calculations are used to select the candidate flame region and measure the temporal motion of flames. These functions are used together to obtain the early flame detection algorithm. The proposed simple algorithm was tested to verify the required function and performance in real-time using IR test videos and a real-time DSP system. The findings indicated that the system detected the flames within 5 to 20 seconds, and had a correct flame detection ratio of 100% with an acceptable false detection ratio in video sequence level.

• 한국건설관리학회논문집
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• 제6권1호
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• pp.80-88
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• 2005

주택수요는 수요유발 상관인자를 주축으로 한 주택수요 예측모형에 의하여 그 수표량을 예측할 수 있다. 이때, 주택수요 예측모형은 상관인자의 영향도에 따라서 인자의 미세한 추이변화에 대해서도 수요의 변화폭을 민감하게 제시하게 된다. 이를 위하여 주택수요 예측에 동원 될 수 있는 여러 상관인자들 가운데 영향도가 가장 큰 인자가 무엇인지 찾아낼 필요가 있다. 이때 대상인자의 데이터는 횡단면자료(Cross Section Data) 혹은 시계열자료(Time Series Data)분석으로 수행된다. 즉, 영향도가 가장 큰 인자들을 찾아내는 방법마련이 필요하며 이후 이 방법에 따른 상관인자의 도출이 가능함에 따라 영향도가 가장 큰 인자를 발굴하는 방법을 제시하고 이에 의한 상관인자를 도출하는 것을 본 연구의 목적으로 한다.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.228-239
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• 2022

Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test