• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.910-917
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• 2007

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper. a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process and recognition Phases. In the Pre-Process Phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. Experimental data was generated by six men employing three types of human touching behaviors including 'hitting', 'stroking' and 'tickling'. As the experimental result of a recognizer being generated for each user and being evaluated as cross-validation, the average recognition rate was 82.9% while the result of a single recognizer for all users showed a 74.5% average recognition rate.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1491-1500
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• 2008

This paper proposes an intelligent surveillance system to recognize suspicious patterns of the human behavior by using the Hidden Markov Model. First, the method finds foot area of the human by motion detection algorithm from image sequence of the surveillance camera. Then, these foot locus form observation series of features to learn the HMM. The feature that is position of the human foot is changed to each code that corresponds to a specific label among 16 local partitions of image region. Therefore, specific moving patterns formed by the foot locus are the series of the label numbers. The Baum-Welch algorithm of the HMM learns each suspicious and specific pattern to classify the human behaviors. To recognize the inputted human behavior pattern in a test image, the probabilistic comparison between the learned pattern of the HMM and foot series to be tested decides the categorization of the test pattern. The experimental results show that the method can be applied to detect a suspicious person prowling in corridor.

• Korean Educational Research Journal
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• v.37 no.1
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• pp.47-66
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• 2016

The purpose of this study is to examine the analysis on the effect of incentive gap of teacher's merit-pay on organizational commitment and organizational citizenship behavior. The study verified the hypothetical path model and analyzed the effects of incentive gap of teacher's merit-pay, organizational commitment and organizational citizenship behavior. The subjects of the study are 762 elementary and secondary school teachers. The results of the study are as follows: Firstly, it was found that there are significant correlations among incentive gap of teacher's merit-pay, organizational commitment and organizational citizenship behavior. Secondly, incentive gap of teacher's merit-pay affects organizational commitment and organizational citizenship behavior. Lastly, S grade teachers of teacher's merit-pay are more organizational commitment and organizational citizenship behavior level were higher than A and B grade teacher. Therefore teacher's merit-pay have positive impacts to the teachers.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.268-276
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• 2021

The purpose of this study was to investigate the effect of the value perception of ecotourism on the behavioral intention and satisfaction of university students. The results of the study are as follows. First, it was found that all ecotourism value recognition factors, such as cognitive value, emotional value, and functional value, had a positive(+) effect on satisfaction. Second, it was found that all ecotourism recognition factors, such as cognitive value, emotional value, and functional value, had a positive(+) effect on behavioral intention. These results show that the higher the awareness of ecotourism is, the higher the satisfaction and behavioral intentions of ecotourism are, but the functional value made up of services, quality, and programs has relatively less influence than other factors. Therefore, various marketing strategies and educational programs such as the development of accessible weekend products and development of sustainable light-emitting products that can respond to each ecotourism value recognition factor that affects the ecotourism product satisfaction and behavior intention should be developed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.6
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• pp.1179-1186
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• 2012

In this paper, we propose an algorithm that recognizes human activity patterns using the human body's joints and the information of the joints. The proposed method extracts the object from inputted video, automatically extracts joints using the ratio of the human body, applies block-matching algorithm for each joint and gets the motion information of joints. The proposed method uses the joints to move, the directional vector of motions of joints, and the sign to represent the increase or decrease of x and y coordinates of joints as basic parameters for human recognition of activity. The proposed method was tested for 8 human activities of inputted video from a web camera and had the good result for the ration of recognition of the human activities.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.241-253
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• 2013

This study investigated the impacts of perceived organizational support and psychological empowerment on organizational citizenship behavior. To accomplish this purpose, the authors conducted a survey of employees in manufacturing companies in the Daegu-Gyeongbuk region. A total of 272 questionnaires were used for the study. Hypotheses were tested through multiple regression analysis. As a result, perceived organizational support and psychological empowerment both positively affected organizational citizenship behavior. Perceived organizational support and psychological empowerment have less been studied as exploratory variables of organizational citizenship behavior. Therefore, the results of this study have many theoretical and practical implications.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.129-141
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• 2010

In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

• Journal of the Korean Applied Science and Technology
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• v.39 no.6
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• pp.883-891
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• 2022

This study is a descriptive survey research attempted to verify the effects of strengths knowledge and self leadership on career preparation behavior in nursing students. The subjects of this study were students enrolled in Department of Nursing in G city. Descriptive statistics, t-test, ANOVA, Pearson's correlation analysis and controlled regression analysis were used for data analysis. The results of the study are as follows. Strengths knowledge(𝛽=.464, p<.001), self leadership(𝛽=.512, p<.001) showed a positive effect on career preparation behavior. The study model accounted for 34.1% of career preparation behavior. These findings suggest that measures to increase strengths knowledge and self leadership are needed to promote career preparation behavior of nursing students.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.923-926
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• 2011

본 연구에서는 움직이는 물체가 있는 비디오에서 검출된 전경 영상(실루엣)을 토대로 사람을 추적하고 추적된 사람의 실루엣 형상을 통하여 활동성을 인식하는 실시간 감시 시스템에 적용 가능한 사람의 행동을 인식하고 분석하고자 한다. 전경에서 블랍(사람)을 검출하는 방법은 기존에 연구했던 차영상을 이용하였고, 검출된 블랍을 대상으로 사람임을 판단하고 사람인 경우 검출된 블랍의 실루엣을 이용한 기존의 자세 추정 기법에 추가적으로 4가지 특징들을 추가하여 사람의 행동을 분석한다. 각 파라미터들은 임계치를 통하여 구분하였다. 본 논문에서는 사람의 행동은 크게 네 가지의 경우로 {Standing, Bending/Crawling, Laying down, Sitting} 분류한다. 제안된 특징 파라미터들을 추가한 방법은 기존의 실루엣 기반의 자세 추정 기법만을 사용하는 것보다 좀더 높은 인식율을 보여주었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.592-593
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• 2022

다중 데이터 기반의 행동 인식 과정에서 데이터 수집 반경이 비교적 제한되는 영상 데이터의 결측에 대한 보완이 요구된다. 본 논문에서는 6축 센서 데이터를 이용하여 결측된 영상 데이터를 생성함으로써 행동 인식의 성능을 개선하는 방법을 제안한다. 가속도와 자이로 센서로부터 수집된 행동 데이터를 이용하여 GAN(Generative Adversarial Network)을 통해 영상에서의 관절(Skeleton) 움직임에 대한 데이터를 생성하고자 한다. 이를 위해 DeepLabCut 기반 모델 학습을 통해 관절 좌표를 추출하며, 전처리된 센서 시퀀스 데이터를 가지고 GRU 기반 GAN 모델을 통해 관절 좌표에 대한 영상 시퀀스 데이터를 생성한다. 생성된 영상 시퀀스 데이터는 영상 데이터의 결측이 발생했을 때 대신 행동 인식 모델의 입력값으로 활용될 수 있어 성능 향상을 기대할 수 있다.