• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.25-57
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• 2020

The purpose of this article is to find out the meanings of library in Korean's daily life, especially considering the ecology of Korean library. To the end this article explores the following three research questions. First, a thorough literature review is conducted to identify the true nature of library recognition in Korean's daily life. The focus is on evaluating the objective reliability of both library statistics and scholarly research on Korean's library recognition. Secondly, evaluated is the level of Korean's library recognition from a relative point of view. A comparative analysis with the library recognition of advanced nations' citizens is carried out to expiscate both special features and limitations in Korean's library recognition. And finally, the indigenous factors influencing Korean's library recognition are investigated, and substantially effective solutions are prescribed to upgrade the level of Korean's library recognition.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.301-307
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• 2020

This study aimed to determine the association between stress recognition and oral symptom experiences among adolescents. We analyzed it, based on the 14th Korea Youth Risk Behavior Web-based Survey (2018), using the chi-square test and logistic regression. The distribution rate of stress recognition and oral symptom experience within one year were 81.7% and 48.9%, respectively. The group with stress recognition had a higher rate (52.2%) of oral symptom experience than the group that did not recognize stress (p<0.001). In the stress recognition group, the odds ratio for oral symptom experience was 1.86 (95% CI: 1.78-1.95). We suggest that stress is associated with oral health in adolescents. In the future, it will be necessary to study stress relief and oral health education in adolescents.

• Journal of the Korean Society of Food Culture
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• v.1 no.3
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• pp.219-229
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• 1986

The consumption of meat processing products in was creased in Korean recently. Morever the demand of tasted meat processing products being gradual increase in general tendency, and so we expect that in the continuing of westernizing for food life and universalizing of urvanism, the demand of meat processing products. In order to improve the marketing strategies for the meat processing industries, consummeris particular behaviors were analyzed as for consummer's recognition, recognition of problem, the evaluation of substitutional proposal, the decision of purchasing intention an purchasing behavior and the evaluation of post-purchasing to the meat processing products.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.55-57
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• 2016

In this paper, we present an algorithm to determine the abnormal behavior through a CCTV-based behavioral recognition and a pattern of hand using ConvexHull. In the existing way that using CCTV for crime prevention, facial recognition is mainly used. Facial recognition is the way that compares the faces that are seen on the screen and faces of criminals for determining how dangerous targets are, however, this way is hard to predict future criminal behavior. Therefore, to predict more various situations, abnormal behaviours are determined with targets' incline of arms, legs and bodys and patterns of hand movements. it can forecast crimes when an acting has been getting within common normality out, comparing whose acting patterns with the crime patterns.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1165-1171
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• 2022

Human behavior recognition using an accelerometer has been applied to various fields. As smartphones have become used commonly, a method for human behavior recognition using the acceleration sensor built into the smartphone is being studied. In the case of the elderly, falling often leads to serious injuries, and falls are one of the major causes of accidents at construction fields. In this article, we proposed recognition method for human falling direction using built-in acceleration sensor and orientation sensor in the smartphone. In the past, it was a common method to use the magnitude of the acceleration vector to recognize human behavior. These days, deep learning has been actively studied and applied to various areas. In this article, we propose a method for recognizing the direction of human falling by applying the deep learning multilayer technique, which has been widely used recently.

• Journal of dental hygiene science
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• v.21 no.1
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• pp.28-37
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• 2021

Background: Career success is the psychological achievement associated with an individual's work. Protean career management behavior is the behavior of managing individual careers in order to achieve individual career goals. The purpose of this study was to clarify the career success of dental hygienists as perceived by clinical dental hygienists and to compare the relationship between career success and protean career management behavior. Methods: Nationwide convenience samples of clinical dental hygienists were obtained; 354 people were surveyed online, and the data of 350 people were finally analyzed. The perception of career success of dental hygienists was assessed using a multiple response method. T-test, ANOVA, and χ2 tests were performed to investigate the differences and relationships between protean career management behavior and career success according to the general characteristics. Results: Career success was recognized by clinical dental hygienists as "income", "work proficiency", "patient consultation", "self-satisfaction", and "recognition by superiors" in order. There were significant differences in protean career management behavior according to general characteristics (p<0.05). Higher career management behavior was common in those higher in age, in married participants, in those with higher educational background, and in those with a higher career, better position, and more job change experience (p<0.05). Among the variables of career success perceived by clinical dental hygienists, "work proficiency" had a significant effect on "career management behavior" (p<0.05). "Work proficiency" and "recognition by superiors" were significant in "protean technological development behavior," and they also influenced actual behavior (p<0.05). Conclusion: The relationship between dental hygienists' career success and protean career management behavior was clarified. Dental hygienists performed career management behaviors to develop work ability and skills. In addition, the relationship between career management behavior and long-term employment was confirmed.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.927-939
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• 2020

Gait recognition can identify people's identity from a long distance, which is very important for improving the intelligence of the monitoring system. Among many human features, gait features have the advantages of being remotely available, robust, and secure. Traditional gait feature extraction, affected by the development of behavior recognition, can only rely on manual feature extraction, which cannot meet the needs of fine gait recognition. The emergence of deep convolutional neural networks has made researchers get rid of complex feature design engineering, and can automatically learn available features through data, which has been widely used. In this paper,conduct feature metric learning in the three-dimensional space by combining the three-dimensional convolution features of the gait sequence and the Siamese structure. This method can capture the information of spatial dimension and time dimension from the continuous periodic gait sequence, and further improve the accuracy and practicability of gait recognition.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2148-2161
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• 2019

In this paper, we present a real-time cattle action recognition algorithm to detect the estrus phase of cattle from a live video stream. In order to classify cattle movement, specifically, to detect the mounting action, the most observable sign of the estrus phase, a simple yet effective feature description exploiting motion history images (MHI) is designed. By learning the proposed features using the support vector machine framework, various representative cattle actions, such as mounting, walking, tail wagging, and foot stamping, can be recognized robustly in complex scenes. Thanks to low complexity of the proposed action recognition algorithm, multiple cattle in three enclosures can be monitored simultaneously using a single fisheye camera. Through extensive experiments with real video streams, we confirmed that the proposed algorithm outperforms a conventional human action recognition algorithm by 18% in terms of recognition accuracy even with much smaller dimensional feature description.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.195-215
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• 2015

Recently, as the number of smart-phone users has been rapidly increased, enterprise managers have a keen interest in business application of social media. Most previous studies have focused on perspective of the individual unit of analysis instead of enterprise level unit. The study is focused on the relationship between the enterprises' recognition and behavioral intention (and use) about social media application. The purpose of this study is to develop the model of small and medium enterprises' social media application, and to find the factors affecting their behavioral intention or use behavior. The moderating effects of four corporate characteristics on the relationship between the enterprises' recognition and behavioral intention are also examined. We surveyed 900 corporate staffs and received 203 responses. After questionnaires with unreliable responses had been excluded, 182 effective samples were used in the final analysis. The findings suggest that Performance Expectation, Social Influence, Facilitating Conditions significantly affect Behavioral Intention of social medea, and Behavioral Intention affects USE. Furthermore, some corporate characteristics have moderating effect on the relationship between recognition of social media and Behavioral Intention.