• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.180-196
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• 2021

The goal of this research is to examine the effects of sports star influencer advertising value on brand equity in social networking sites. In particular, this study identifies the moderating role of consumer team identification. A total of 350 university students participated via online survey. To test proposed hypotheses, confirmatory factor analysis, structural equation modeling, and multi-group analysis were employed. It was found that informativeness, entertainment, and credibility showed significant positive effects on brand equity. Also, significant moderation effects of team identification were found in that consumers with high team identification compared to those with low team identification perceived higher value of entertainment. On the other hand, consumers with low team identification perceived more irritation than those with high team identification. This study contributes to the understanding of sports star influencer advertising in social networking sites. Theoretical and practical implications as well as suggestions for future research in this area are provided.

• Journal of Distribution Science
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• v.17 no.3
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• pp.57-67
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• 2019

Purpose - This study aims to examine the impact of work values on entrepreneurial attitudes, and test the moderating effect of entrepreneurial opportunity identification on the above mentioned relationship as well. Research design, data, and methodology - A questionnaire survey was conducted to 258 employees who comes from 8 different types of the enterprises in northwestern of China, and the corresponding research model was verified. Results - The results show that "comfort and security" (one dimension of work values) has a significant negative impact on entrepreneurial attitudes. Another two dimensions of work values, such as "competence and growth" and "status and independence" have a significant positive impact on entrepreneurial attitudes. In addition, entrepreneurial opportunity identification has a significant moderating effect on the relations between work values and entrepreneurial attitudes. Specifically, only the entrepreneurship opportunity identification positively moderates the relationship between status & independence and entrepreneurial attitudes. Conclusions - This research further enriches the relevant theories of organizational behavior and entrepreneurships. This study also has guiding significance and value for management practice, especially for this research results implies, that is, individual's ability to entrepreneurial opportunity identification (e.g., identify feasible distribution channel for potential new venture) is important in entrepreneurship.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.655-664
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• 2019

In this paper, we propose a novel way of combining multiple deep convolutional neural network (DCNN) architectures which work well for accurate video face identification by adopting a serial combination of 3D and 2D DCNNs. The proposed method first divides an input video sequence (to be recognized) into a number of sub-video sequences. The resulting sub-video sequences are used as input to the 3D DCNN so as to obtain the class-confidence scores for a given input video sequence by considering both temporal and spatial face feature characteristics of input video sequence. The class-confidence scores obtained from corresponding sub-video sequences is combined by forming our proposed class-confidence matrix. The resulting class-confidence matrix is then used as an input for learning 2D DCNN learning which is serially linked to 3D DCNN. Finally, fine-tuned, serially combined DCNN framework is applied for recognizing the identity present in a given test video sequence. To verify the effectiveness of our proposed method, extensive and comparative experiments have been conducted to evaluate our method on COX face databases with their standard face identification protocols. Experimental results showed that our method can achieve better or comparable identification rate compared to other state-of-the-art video FR methods.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.375-382
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• 2006

This paper is about how to identify emotional information and how to detect a specific emotion from speech signals. For emotion identification and detection task. we use long-term acoustic feature parameters and select the optimal Parameters using the feature selection technique based on F-score. We transform the conventional SVM into probabilistic output SVM for our emotion identification and detection system. In this paper we propose three approximation methods for log-likelihoods in a hypothesis test and compare the performance of those three methods. Experimental results using the SUSAS database showed the effectiveness of both feature selection and Probabilistic output SVM in the emotion identification task. The proposed methods could detect anger emotion with 91.3% correctness.

• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.131.2-131
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• 2001

No Abstract, See Full Text

• Journal of the Korea Institute of Military Science and Technology
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• v.8 no.1 s.20
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• pp.39-48
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• 2005

After the development of the Firefly, flight tests have been performed to verify the performance and get the parameters for the mathematical model of the aircraft. The flight test data is used to get parameters for the mathematical model of the aircraft through the parameter identification process. An arbitrary control input is applied to the test flight which is a part of parameter identification process. A square wave has been used a control input which is called Doublet signal. The aspect of the signal is same length and magnitude in both (+) and (-) directions such as sine wave. The Doublet signal is composed of a dominant frequency and many high frequencies, so that it is appropriate signal to excite the motion of an aircraft. In this paper, the control input of the flight test data has been analyzed to check the efficiency of the control input using DFT(Discrete Fourier Transform). From the result of analysis, an alternative input was extracted.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.877-884
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• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2011.04a
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• pp.228-230
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• 2011

2자유도 풍동실험으로부터 플러터계수를 추출하기 위해서 MITD, MULS와 같은 다양한 기법들이 활용되고 있다. 이러한 기법들은 부분측정(partial measurement)을 기반으로 한 state-space model을 이용하고 있다. 여기서는 완전측정(full measurement)를 기반으로 한 동방정식상의 최소화 기법인 EEE 방법을 제시한다. EEE 기법을 B/D=20의 구형 단면에 적용하고 MITD를 이용한 결과와 비교하여 제안한 방법의 타당성과 실교량에서 적용 가능성을 검증하고자 한다.

• Journal of the Ergonomics Society of Korea
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• v.15 no.1
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• pp.53-67
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• 1996

Since Romberg's test in 1953, the analysis of postural sway during upright stance has been widely used as a tool for evaluating balance and disorders of the postural control system. This review describes the methods that have been used to evaluste the static and dynamic performance of the postural control system. Various identification methods of postural control system based on standing balance are discussed and measures of postural sway are described. The application areas of standign balance research, with an emphasis on postural control evaluations, are also briefly described. This review can be used to gain an understanding of the dynamics of human standing balance.

• The korean journal of orthodontics
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• v.32 no.2 s.91
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• pp.79-89
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• 2002

The purpose of this study is to evaluate the reproducibility and errors in landmark identification of conventional lateral cephalometric radiography and digital lateral cephalometric radiography. Fifteen conventional lateral cephalometric radiographs and fifteen digital lateral cephalometric radiographs were selected in adults with no considerations on sex and craniofacial forms. Each landmark was identified and expressed as the coordinate (x, y). The landmarks were classified into 3 groups. The landmarks of the first identification was T1, identification after one week was T2, and identification after one month was T3. The mean and standard deviation of identification errors between replicates were calculated according to the x and y coordinates. The errors between first identification and second identification were expressed as T2-T1(x), T2-T1(y) and those between first identification and third identification were expressed as T3-T1(x), T2-T1(y). Each was divided into conventional lateral cephalometric radiography and digital lateral cephalometric radiography. The independent t- test was used for statistical analysis of identification errors for the evaluation of reproducibility. The results of this study were as follows ; 1. Generally, the mean and standard deviation of landmark identification errors in digital lateral cephalometric radiography was smaller than those of conventional lateral cephalometric radiography. 2. Only a few landmarks showed statistically significant difference in identification error between conventional lateral cephalometric radiography and digital lateral cephalometric radiography. 3. The enhancement of image quality didn't guarantee decrease in landmark identification error and didn't affect tendency of landmark identification error.