• Journal of Korean Academy of Nursing Administration
• /
• v.1 no.1
• /
• pp.79-96
• /
• 1995

A human being as a client has been understood only through a western cultural view so far, now we put forth efforts to set up the concept which is suitable for our korean nursing situation. This paper was reviewed to discover Korean behavior pattern through the concept of the human being in Korean traditional thoughts to keep in pace with above idea and develope the stem of the nursing knowledge. Behavior pattern usually has two aspects, the one is unconscious behavior which conform to old custom and the other is conscious one which abide by a conventional rule. The former was considered through the concept of human being in Tan-kun mythodology, Divination, Tong-hak (Cheondoism) and the latter was Buddism, Confucianism, Sung-ri hak (Human nature and natural Laws), Sil-hak (The rule of Heaven philosophy). Through these traditional thoughts, we can lead Humanity, Present-oriented, Family-focused, Ranking-centered, Fatalism, Projection in Korean behavior pattern and unconscious behavior correspond to the Naturalistic human being, conscious to Societic human being as well. Even though Korean behavior patterns were changed to the times, we found that Korean natural characteristics were remained in the of unconscious-conscious behavior. This point must be considered for caring a client better than anything else in our nursing situiation.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.6
• /
• pp.701-708
• /
• 2018

Human error is an important cause of maritime accidents and the identification of human error is fundamental to maritime-accident preventions. In particular, the pattern of technical behavior taken in the circumstance of bridge teams(navigator & helmsman) provides important information to identify human error. The purpose of this study is to identify and analyze technical behavior pattern of bridge teams using Williamson's turn for rescue of persons overboard. The focus of this study is to build and analyze a cognitive model of the human behavior factors of the bridge teams in the process of implementing the experiments. The experimental environment was constructed using a ship-handling simulator and conducted an experiment on participants from 24 bridge teams. As a result of the experiment, it was able to identify the behavior pattern of the ship's maneuvering and maintain trajectory using the rudder and engine. This study is expected to correct human error in the bridge teams application to the certification and training of seafarers.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.491-496
• /
• 2003

This paper proposes modeling of human behavior and a method of finding irregular human behavior. At first, human behavior model is proposed by paying attention to habitual human behavior at home. Generally, it is difficult to obtain the information of individual life pattern because of high cost for setting sensors such as cameras to observe human action. Therefore we capture turning on/off consumer electronic equipments as actual human behavior action, where some or many consumer electric equipments were used such as television, room light, video and so on in our daily life. Noting that are some relations between turning on/off those consumer electric equipments and our action, we proposes how to construct a human behavior knowledge by analyzing human behavior based on observation of human habitual life. Also an algorithm to identify on find irregular behavior different from habitual life behavior are described. Finally, the significance of the proposed method is shown by some experimental results.

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

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.5
• /
• pp.1304-1310
• /
• 2008

The purpose of this study is to propose the system architecture of intelligent ubiquitous house which is able to team the human behavior by itself and to predict the forthcoming situation, and to provide the customized and personalized service based on human behavior. The suggestions for advanced intelligent ubiquitous house are as follows; 1) Service should be combined with dwellers' behavior pattern, location moving pattern and service pattern in order to provide the personalized and customized service. 2) The system should be equipped with 4 components such as Agent, Database, Working Memory, and Log Data. Especially. This proposed system architecture of advanced ubiquitous house, which are equipped with these 4 components, will be the basis of providing customized service to every dwellers by learning dwellers' behavior pattern, accumulating dwellers' information, and recognizing dweller's lift style as time goes by.

• Korean Institute of Interior Design Journal
• /
• no.28
• /
• pp.60-67
• /
• 2001

Built-up environments by humans are cultural byproducts which combine social ideology and architectural paradigm. The process of modernization in the Western countries has the characteristic of decisive paradgm based on materialism. Therefore, environmental design in modern world failed to focus on the essential features of humanity which are the subject of space and replaced it for objective and unilateral architectural environments, instead. Environment without supporting the human psychological and complicated behaviorism is as same as the hardware without the vitality. under these regards, this study will cover the design approach of pattern language as a design method of environment design. The purpose of design approach by pattern language lies in creating the space of flexibility, adaptability and strong vitality. It is summed up as humanization in space and it helps the user to verbalize individualized space language for their own. The range and method of in the study attribute to the pattern language of Christopher Alexander and a researcher' method on them. In premise that human behavior ought to the multilateral and indefinite under rapid change of circumstances in modern world, th study tried to find the design method stimulating creative behavior of human being.

• ETRI Journal
• /
• v.44 no.3
• /
• pp.426-437
• /
• 2022

To understand the multilateral characteristics of human behavior and physiological markers related to physical, emotional, and environmental states, extensive lifelog data collection in a real-world environment is essential. Here, we propose a data collection method using multimodal mobile sensing and present a long-term dataset from 22 subjects and 616 days of experimental sessions. The dataset contains over 10 000 hours of data, including physiological, data such as photoplethysmography, electrodermal activity, and skin temperature in addition to the multivariate behavioral data. Furthermore, it consists of 10 372 user labels with emotional states and 590 days of sleep quality data. To demonstrate feasibility, human activity recognition was applied on the sensor data using a convolutional neural network-based deep learning model with 92.78% recognition accuracy. From the activity recognition result, we extracted the daily behavior pattern and discovered five representative models by applying spectral clustering. This demonstrates that the dataset contributed toward understanding human behavior using multimodal data accumulated throughout daily lives under natural conditions.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.12
• /
• pp.123-129
• /
• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• Journal of the Korean Home Economics Association
• /
• v.47 no.6
• /
• pp.1-10
• /
• 2009

This study investigated the influence of children's emotional expression and sociability, and their mothers' communication pattern on their prosocial behavior. The participants were 65 preschool children aged between 5 and 6, and their mothers. Each child-mother dyad was observed for 30 minutes in a lab setting, which was designed to evaluate the child's socioemotional competence and the mother's socialization behavior. Videotaped data were analyzed by two coders for aspects of sharing behavior, the expression of happiness, sadness, anger, anxiety, and sociability for children, and mothers' communication strategies. Results showed that children's anger and anxiety expression were the most significant predictors for their prosocial behavior. Mothers' punitive communication pattern negatively affected children's prosocial behavior. However, when compared to the children's emotional expression, its' accountability were not significant. The influence of negative emotions, and its' adverse role in interpersonal interactions are discussed.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.12
• /
• pp.1214-1218
• /
• 2010

As a study on activities associated with sleeping, this paper is aimed to trace a behavior log by differentiating human behavior patterns. Toward this research purpose, we define a behavior log and a simplified feature vector about human behavior patterns associated with sleeping. Then, based on thresholds of the feature vector, we did experiments applying the individual-base behavior pattern decision algorithm to human behavior patterns. The important results derived from these experiments indicate that the proposed approach reflecting individual behavioral characteristics is more useful than the existing single group approach.