• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1213-1229
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• 2016

Cho and Shin (2016) recently demonstrated that an integrated HAR model has a forecast advantage over the HAR model of Corsi (2009). Recalling that realized volatilities of financial assets have asymmetries, we add a leverage term to the integrated HAR model, yielding the LIHAR model. Out-of-sample forecast comparisons show superiority of the LIHAR model over the HAR and IHAR models. The comparison was made for all the 20 realized volatilities in the Oxford-Man Realized Library focusing specially on the DJIA, the S&P 500, the Russell 2000, and the KOSPI. Analysis of the realized volatility data sets reveal apparent long-memory and asymmetry. The LIHAR model takes advantage of the long-memory and asymmetry and produces better forecasts than the HAR, IHAR, LHAR models.

• The Journal of the Korea Contents Association
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• v.15 no.10
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• pp.1-9
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• 2015

In this paper, a study on facial movements are analyzed in terms of opposite emotion stimuli by image processing of Kinect facial image. To induce two opposite emotion pairs such as "Sad - Excitement"and "Contentment - Angry" which are oppositely positioned onto Russell's 2D emotion model, both visual and auditory stimuli are given to subjects. Firstly, 31 main points are chosen among 121 facial feature points of active appearance model obtained from Kinect Face Tracking SDK. Then, pixel changes around 31 main points are analyzed. In here, local minimum shift matching method is used in order to solve a problem of non-linear facial movement. At results, right and left side facial movements were occurred in cases of "Sad" and "Excitement" emotions, respectively. Left side facial movement was comparatively more occurred in case of "Contentment" emotion. In contrast, both left and right side movements were occurred in case of "Angry" emotion.

• International journal of steel structures
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• v.18 no.5
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• pp.1541-1559
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• 2018

This paper addresses the dynamic loading characteristics of the shock tube onto sandwich steel beams as an efficient and accurate alternative to time consuming and complicated fluid structure interaction using finite element modeling. The corrugated sandwich steel beam consists of top and bottom flat substrates of steel 1018 and corrugated cores of steel 1008. The corrugated core layers are arranged with non-uniform thicknesses thus making sandwich beam graded. This sandwich beam is analogous to a steel beam with web and flanges. Substrates correspond to flanges and cores to web. The stress-strain relations of steel 1018 at high strain rates are measured using the split-Hopkinson pressure. Both carbon steels are assumed to follow bilinear strain hardening and strain rate-dependence. The present finite element modeling procedure with an improved dynamic impulse loading assumption is validated with a set of shock tube experiments, and it provides excellent correlation based on Russell error estimation with the test results. Four corrugated graded steel core arrangements are taken into account for core design parameters in order to maximize mitigation of blast load effects onto the structure. In addition, numerical study of four corrugated steel core placed in a reverse order is done using the validated finite element model. The dynamic behavior of the reversed steel core arrangement is compared with the normal core arrangement for deflections, contact force between support and specimen and plastic energy absorption.

• Journal of the Korean Society for information Management
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• v.26 no.4
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• pp.227-248
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• 2009

In this study, description elements of National Archives of Korea(NAK) and National Assembly Archives(NAA) were collected and analysed based on PDI(Preservation Description Information) of OAIS Reference Model(ISO 14721). As for NAK, records management guideline published in 2009 and metadata standards published in 2007 were analysed. As for NAA, Records management manual published in 2009 and metadata applied in national assembly records management system were analysed with group interviews. As a result, improved metadata details and sub-elements were suggested based on OAIS PDI concepts and Calanag's and Russell's research.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1155-1163
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• 2009

This paper proposes an automatic facial expression generation system of vector graphic character using gaussian process model. Proposed method extracts the main feature vectors from twenty-six facial data of character redefined based on Russell's internal emotion state. Also by using new gaussian process model, SGPLVM, we find low-dimensional feature data from extracted high-dimensional feature vectors, and learn probability distribution function (PDF). All parameters of PDF are estimated by maximization the likelihood of learned expression data, and these are used to select wanted facial expressions on two-dimensional space in real time. As a result of simulation, we confirm that proposed facial expression generation tool is working in the small facial expression datasets and can generate various facial expressions without prior knowledge about relation between facial expression and emotion.

• Journal of Astronomy and Space Sciences
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• v.1 no.1
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• pp.67-74
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• 1984

Photoelectric UBV light curves of AR lacertae made in one season during 1981-82 are presented. Although the shape of the light curves in the outside eclipses shows a strong distortion, the scatter of observations as well as phase coverage are better than those previously available. Fourier coefficients are derived from the V-light curve and the observed curve successfully rectified to the Russell model. Light curve solutions are computed and the geometrical and physical parameters of AR Lac are derived as $a_s$=0.182, $a_g$=0.341, j=$86^{circ}$3, $L_s$=0.372, $L_g$=0.628, k=0.53, $X_s$=0.85, $X_g$=0.4.

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.113-120
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• 2016

People use social media platforms such as Twitter to leave traces of their personal thoughts and opinions. In other words, social media platforms retain the emotions of the people as it is, and accurately understanding the emotions of the people through social media will be used as a significant index for disaster management. In this research, emotion type modeling method and emotional quotient quantification method will be proposed to understand the emotions present in social media platforms. Emotion types are primarily analyzed based on 3 major emotions of affirmation, caution, and observation. Then, in order to understand the public's emotional progress according to the progress of disaster or accident and government response in detail, negative emotions are broken down into anxiety, seriousness, sadness, and complaint to enhance the analysis. Ultimately, positive emotions are further broken down into 3 more emotions, and Russell emotion model was used as a reference to develop a model of 8 primary emotions in order to acquire an overall understanding of the public's emotions. Then, the emotional quotient of each emotion was quantified. Based on the results, overall emotional status of the public is monitored, and in the event of a disaster, the public's emotional fluctuation rate could be quantitatively observed.

• Child Studies in Asia-Pacific Contexts
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• v.4 no.1
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• pp.1-12
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• 2014

Emotion is a central feature of social interactions. In this study, we examined age-related changes in emotion expressiveness and emotion knowledge and how young children's emotion expressiveness and knowledge were related. A total of 300 children attending a daycare center contributed data for the study. Observation and interview data relevant to measures of emotion expressiveness and knowledge were collected and analyzed. Both emotion knowledge and expressed positive affect increased with age. Older preschool children expressed positive affect more frequently than did younger preschoolers. Older preschool children also labeled, recognized, and provided plausible causes mores accurately than did younger preschool children. In addition, we tested whether children's errors on the free labeling component conform to the structural model previously suggested by Bullock and Russell (1986) and found that preschool children were using systematic strategies for labeling emotion states. Relations between emotion expressiveness and emotion knowledge generally were not significant, suggesting that emotional competence is only gradually constructed by the child over the preschool years.

• Bulletin of the Korean Space Science Society
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• 2004.10b
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• pp.243-246
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• 2004

We calculate theoretical isochrones in a consistent way for five filters near the K-band, K, K', $K_s$, F205W, and F222M. Even when displayed in the same Vega magnitude system, the near-infrared colors of the same isochrone can differ by up to 0.18 mag at its bright end, depending on the filter. We analyze isochrones for several different extinction values, and find that a care is needed when comparing extinction values that are estimated by different filter sets, in particular when comparing those between atmospheric and space filter sets. To alleviate this problem, we present an 'effective extinction law' for each filter set and isochrone model, which describes extinction behaviour of isochrones in the observed color-magnitude diagram.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1496-1505
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• 2018

The technology of emotion recognition is necessary for human computer interaction communication. There are many cases where one cannot communicate without considering one's emotion. As such, emotional recognition technology is an essential element in the field of communication. n this regard, it is highly utilized in various fields. Various bio-sensor sensors are used for human emotional recognition and can be used to measure emotions. This paper proposes a system for recognizing human emotions using two physiological sensors. For emotional classification, two-dimensional Russell's emotional model was used, and a method of classification based on personality was proposed by extracting sensor-specific characteristics. In addition, the emotional model was divided into four emotions using the Support Vector Machine classification algorithm. Finally, the proposed emotional recognition system was evaluated through a practical experiment.