• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.629-642
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• 2013

Recently, with the advent of smart phones, it brought many changes in lives of modern people. Especially, application utilizing the sensor information of smart phone, which provides the service adapted by user situations, has been emerged. Sensor data of smart phone can be used for recognizing the user situation, Because it is closely related to the behavior and habits of the user. currently, GPS sensor one of mobile sensor has been utilized a lot to recognize basic user activity. But, depending on the user situation, activity recognition system cannot receive GPS signal, and also not collect received data. So utilization is reduced. In this paper, for solving this problem, we suggest a method of user activity recognition that focused on the accelerometer sensor data using smart phone. Accelerometer sensor is stable to collect the data and it's sensitive to user behavior. Finally this paper suggests a noble approach to use state transition diagrams which represent the natural flow of user activity changes for enhancing the accuracy of user activity recognition.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.25-32
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• 2015

With the increased frequency of crime such as assaults and sexual violence, the reliance on CCTV in arresting criminals has increased as well. However, CCTV, which should be monitored by human labor force at all times, has limits in terms of budget and man-power. Thereby, the interest in intelligent security system is growing nowadays. Expanding the techniques of an objects behavior recognition in previous studies, we propose a system to detect forms of violence between 2~3 objects from images obtained in CCTV. It perceives by detecting the object with the difference operation and the morphology of the background image. The determinant criteria to define violent behaviors are suggested. Moreover, provable decision metric values through measurements of the number of violent condition are derived. As a result of the experiments with the threshold values, showed more than 80% recognition success rate. A future research for abnormal behaviors recognition system in a crowded circumstance remains to be developed.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.151-163
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• 2019

The purpose of this study was to investigate the effects of safety culture on the safety consciousness and safety behaviors of manufacturing workers, and to suggest ways for manufacturing workers to understand the safety culture and improve safety consciousness and safety behavior. To achieve this research objective, out of 176 industrial complexes in Seoul and Gyeonggi Province registered with the Korea Industrial Complex Corporation, workers at 50 industrial complexes, including the Korea Export-Industrial Complex and Seoul's Onsuji, were subject to research. The implementation of this survey distributed 300 questionnaires through the mid-level managers of manufacturers and environment safety and health managers over a period of one month from August 1st to 31st, 2019, finally statisticalizing the data in 282 parts excluding 18 questionnaires deemed to have been unresponsive. First, the safety culture (safety climate, safety procedures) has a positive effect on the safety consciousness (recognition of importance, interest and participation inducement) of the manufacturing workers. Second, the safety culture (safety climate, safety procedures) has a positive effect on the safety behavior (safety planning, safety check) of manufacturing workers. Third, safety consciousness (recognition of importance, interest and inducement of participation) has a positive influence on the safety behavior (safety planning, safety check) of manufacturing workers. Fourth, the safety consciousness (recognition of importance, interest and inducement of participation) appears to have a partial mediating effect in relation to safety culture (safety climate, safety procedure) and safety behavior (safety planning, safety check) of manufacturing workers. The implication of this study is that although the industrial accidents have occurred in the manufacturing industry in recent years, the studies on the workers in the manufacturing industry are insufficient. However, this study is meaningful that it has suggested ways for manufacturing workers to understand the safety culture and improve the safety consciousness and safety behavior by analyzing the effects of safety culture on safety consciousness and safety behavior of manufacturing workers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1061-1068
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• 2012

This study was a descriptive survey to examine the impact of spouse's conflict-coping behavior on self-esteem and depression among couples married within 5 years, in order to provide data for education and intervention program of improving their relationships for early marriage couples. Participants were 176 persons who were family members or neighborhood of S college students in Seoul and they were asked to complete questionnaires. Findings showed that there were differences in conflict-coping behavior of withdrawal type according to sex while differences in conflict-coping behavior of physical type and withdrawal type and depression according to age. Differences were found in conflict-coping behavior of language type and depression according to occupation. There were significant differences in self-esteem and depression according to couples' conversation time. Perceived their spouses cope with the conflict in the relationship between behavior and depression, self-esteem appeared to represent an indirect effect.

• Journal of Animal Science and Technology
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• v.63 no.6
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• pp.1453-1463
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• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.

• Smart Media Journal
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• v.13 no.5
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• pp.19-25
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• 2024

The biggest type of behavior that prevents people with developmental disabilities from entering society is aggressive behavior. Aggressive behavior can pose a threat not only to the personal safety of the person with a developmental disability, but also to the physical safety of others. In this study, we propose a wearable system using a low-power processor. The proposed system uses an IMU (Inertial Measurement Unit) to analyze user behavior, and when attack behavior is not detected for a certain period of time through an LED array attached to the developed system, an interesting LED is displayed. By expressing patterns, we provide behavioral intervention through compensation to people with developmental disabilities. In order to implement a system that must be worn for a long time in a power-limited environment, we present a method to optimize performance and energy consumption across all stages, from data preprocessing to AI model application.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.771-778
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• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• Korean journal of food and cookery science
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• v.22 no.6 s.96
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• pp.840-848
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• 2006

To analyse the impact of recognition for local food on frequency of visiting for local food restaurants, we surveyed 333 residents in the Kyungsangdo areas. The findings are summarized as follows. On interest of native foods, 'much' scored 40.6% and 'taste' scored 32.9%, in requirement of development. The criteria of selection of local foods was 62.3% in 'taste'. 'Institute(municipal government)' scored 31.3% as the main responsible body for the succession of local foods. The most significant criterion for tourism product of local foods was 'taste'(34.5%). The most effective way to popularize the local foods was to 'hold various kinds of cultural events'(27.5%). The necessity score on tourism product of local foods was 3.55 points. The highest recognition on native local foods was 'succession to next generation'(3.96 points). The most influential variable affecting the visit frequency toward local food restaurants was 'health factor'.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.345-354
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• 2021

Recently, deep learning-based image recognition systems have been adopted to various surveillance environments, but most of them are still picture-type object recognition methods, which are insufficient for the long term temporal analysis and high-dimensional situation management. Therefore, we propose a method recognizing the specific dangerous situation generated by human in real-time, and utilizing deep learning-based object analysis techniques. The proposed method uses deep learning-based object detection and tracking algorithms in order to recognize the situations such as 'trespassing', 'loitering', and so on. In addition, human's joint pose data are extracted and analyzed for the emergent awareness function such as 'falling down' to notify not only in the security but also in the emergency environmental utilizations.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.248-251
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• 2015

High injury and fatality rates remain a serious problem in the construction industry. Many construction injuries and fatalities can be prevented if workers can recognize potential hazards and take actions in time. Many efforts have been devoted in improving workers' ability of hazard recognition through various safety training and education methods. However, a reliable approach for evaluating this ability is missing. Previous studies in the field of human behavior and phycology indicate that the visual focus of attention (VFOA) is a good indicator of worker's actual focus. Towards this direction, this study introduces an automated approach for estimating the VFOA of equipment operators using a head orientation-based VFOA estimation method. The proposed method is validated in a virtual reality scenario using an immersive head mounted display. Results show that the proposed method can effectively estimate the VFOA of test subjects in different test scenarios. The findings in this study broaden the knowledge of detecting the visual focus and distraction of construction workers, and envision the future work in improving work's ability of hazard recognition.