• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.961-968
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• 2018

Recently, researches on automatic recognition of human activities have been actively carried out with the emergence of various intelligent systems. Since a large amount of visual data can be secured through Closed Circuit Television, it is required to recognize human behavior in a dynamic situation rather than a static situation. In this paper, we propose new intelligent human activity recognition model using the trajectory information extracted from the video sequence. The proposed model consists of three steps: segmentation and partitioning of trajectory step, feature extraction step, and behavioral learning step. First, the entire trajectory is fuzzy partitioned according to the motion characteristics, and then temporal features and spatial features are extracted. Using the extracted features, four pedestrian behaviors were modeled by decision tree learning algorithm and performance evaluation was performed. The experiments in this paper were conducted using Caviar data sets. Experimental results show that trajectory provides good activity recognition accuracy by extracting instantaneous property and distinctive regional property.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.417-424
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• 2012

In this paper, we propose an automatic system that recognizes dynamic human gestures activity, including Arabic numbers from 0 to 9. We assume the gesture trajectory is almost in a plane that called principal gesture plane, then the Least Squares Method is used to estimate the plane and project the 3-D trajectory model onto the principal. An improved FNN model combined with HMM is proposed for dynamic gesture recognition, which combines ability of HMM model for temporal data modeling with that of fuzzy neural network. The proposed algorithm shows that satisfactory performance and high recognition rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3328-3349
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• 2020

With rapid development of ubiquitous computing and location-based services (LBSs), human trajectory data and associated activities are increasingly easily recorded. Inappropriately publishing trajectory data may leak users' privacy. Therefore, we study publishing trajectory data while preserving privacy, denoted privacy-preserving activity trajectories publishing (PPATP). We propose S-PPATP to solve this problem. S-PPATP comprises three steps: modeling, algorithm design and algorithm adjustment. During modeling, two user models describe users' behaviors: one based on a Markov chain and the other based on the hidden Markov model. We assume a potential adversary who intends to infer users' privacy, defined as a set of sensitive information. An adversary model is then proposed to define the adversary's background knowledge and inference method. Additionally, privacy requirements and a data quality metric are defined for assessment. During algorithm design, we propose two publishing algorithms corresponding to the user models and prove that both algorithms satisfy the privacy requirement. Then, we perform a comparative analysis on utility, efficiency and speedup techniques. Finally, we evaluate our algorithms through experiments on several datasets. The experiment results verify that our proposed algorithms preserve users' privay. We also test utility and discuss the privacy-utility tradeoff that real-world data publishers may face.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.934-936
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• 2013

A routing scheme for a group of mobile users for wireless ad-hoc networks is presented. The proposed scheme mines social activity patterns from wireless traces, and exploits social user group for efficient data routing among users based on a data publish approach. Simulation results based on real-world wireless traces show that our routing scheme reduces routing cost for a large mobile user group with a factor of 1.8 compared to a baseline counterpart.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.310-320
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• 2005

This study attempts at prototyping and evaluating a geovisualization tool that summarizes and explores human activity patterns using spatio-temporal trajectory data collected from GPS receiver. A set of core conceptualization developed in 'time geography' is successfully represented by our prototype based on the notion of 'space-time cube.' The notions of 'temporal dispersion cylinder' and 'parallel plane plot' are also implemented to allow funker analyses of human activity pattern on the space-time trajectory. The capabilities of the geovisualization environment we proposed include the interactive and dynamic functions that support a variety of explorations on the three components of spatio-temporal data : space(where), time(when), and object(what).

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.498-502
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• 1986

A generalized singular linear quadratic control technique is developed to design an optimal trajectory tracking system. The output feedback control law is designed using this technique. The feedback gain matrix is synthesized to minimize tracking errors with pole placement capability to satisfy the control activity requirements. An applications to a bank-to-turn missile coordinated autopilot system design is presented.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.10-15
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• 2007

This paper proposes the method that detects abnormal trajectory of fish with tracking data. And it is obtained by automatic tracking system based on conventional computer vision. Also, we analyze the trajectory using subband frequency features through DWT(Discrete Wavelet Transform). Through experimental results, we confirm that our results have some statistical means. The proposed method demonstrates that DWT is useful method for detecting presence of toxicoid features in environment as for an alternative of bio-monitoring tool.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3197-3218
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• 2012

Compared with traditional itinerary planning, intention-oriented itinerary recommendations can provide more flexible activity planning without requiring the user's predetermined destinations and is especially helpful for those in unfamiliar environments. The rank and classification of points of interest (POI) from location-based social networks (LBSN) are used to indicate different user intentions. The mining of vehicles' physical trajectories can provide exact civil traffic information for path planning. This paper proposes a POI category-based itinerary recommendation framework combining physical trajectories with LBSN. Specifically, a Voronoi graph-based GPS trajectory analysis method is utilized to build traffic information networks, and an ant colony algorithm for multi-object optimization is implemented to locate the most appropriate itineraries. We conduct experiments on datasets from the Foursquare and GeoLife projects. A test of users' satisfaction with the recommended items is also performed. Our results show that the satisfaction level reaches an average of 80%.

• Women's Health Nursing
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• v.28 no.2
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• pp.123-133
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• 2022

Purpose: This study investigated the trajectory of subjective health status in married postmenopausal women and aimed to identify predictive factors affecting subjective health status. Methods: Data were obtained from women who participated in wave 4 (2012) of the Korean Longitudinal Survey of Women & Families Longitudinal Study and continued to the latest phase (wave 7, 2018). A latent growth model (LGM) was used to analyze data from 1,719 married postmenopausal women in the framework of the ecological system theory. Results: The mean age of the participants at wave 4 was 56.39±4.71 years, and the average subjective health status was around the midpoint (3.19±0.84). LGM analysis confirmed that subjective health status decreased over time (initial B=3.21, slope B=-0.03). The factors affecting initial subjective health were age, body mass index, frequency of vigorous physical activity (microsystem level), marital satisfaction (mesosystem level), and medical service utilization (macrosystem level). Medical service utilization and the frequency of vigorous physical activity were identified as predictive factors affecting the slope in subjective health status. The model fit was satisfactory (TLI=.92, CFI=.95, and RMSEA=.04). Conclusion: This analysis of the trajectory of subjective health status of married postmenopausal women over time confirmed that subjective health is influenced by overall ecological system factors, including the microsystem, mesosystem, exosystem, macrosystem, and chronosystem. Therefore, it is necessary to assess physical activity and support policies promoting access to medical services in order to improve the subjective health status of married postmenopausal women.

• Proceedings of the Korea Society for Simulation Conference
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• 2004.05a
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• pp.109-117
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• 2004

In this paper, we consider the aortic sinus baroreceptor, which is the most representative baroreceptor sensing the variance of pressure in the cardiovascular system, and propose heart activity control model to observe the effect of delay time in heart period and stroke volume under the regulation of baroreflex in the aortic sinus. The proposed heart activity baroreflex regulation model contains electric circuit sub-model. We constituted the time delay sub-model to observe sensitivity of heart activity baroreflex regulation model by using the variable value to represent the control signal transmission time from the output of baroreflex regulation model to efferent nerve through central nervous system. The simulation object of this model is to observe variability of the cardiovascular system by variable value in time delay sub-model. As simulation results, we observe three patterns of the cardiovascular system variability by the time delay, First, if the time delay over 2.5 second, aortic pressure and stroke volume and heart rate is observed nonperiodically and observed. Finally, if time delay under 0.1 second, then heart rate and aortic pressure-heart rate trajectory is maintained in stable state.