• ETRI Journal
• /
• v.36 no.4
• /
• pp.662-672
• /
• 2014

Human action recognition is used in areas such as surveillance, entertainment, and healthcare. This paper proposes a system to recognize both single and continuous human actions from monocular video sequences, based on 3D human modeling and cyclic hidden Markov models (CHMMs). First, for each frame in a monocular video sequence, the 3D coordinates of joints belonging to a human object, through actions of multiple cycles, are extracted using 3D human modeling techniques. The 3D coordinates are then converted into a set of geometrical relational features (GRFs) for dimensionality reduction and discrimination increase. For further dimensionality reduction, k-means clustering is applied to the GRFs to generate clustered feature vectors. These vectors are used to train CHMMs separately for different types of actions, based on the Baum-Welch re-estimation algorithm. For recognition of continuous actions that are concatenated from several distinct types of actions, a designed graphical model is used to systematically concatenate different separately trained CHMMs. The experimental results show the effective performance of our proposed system in both single and continuous action recognition problems.

• Journal of the Chungcheong Mathematical Society
• /
• v.10 no.1
• /
• pp.161-175
• /
• 1997

We classify free actions of finite abelian groups on the 3-dimensional nilmanifold, up to topological conjugacy. By the works of Bieberbach and Waldhausen, this classification problem is reduced to classifying all normal subgroups of almost Bieberbach groups of finite index, up to affine conjugacy.

• Bulletin of the Korean Mathematical Society
• /
• v.57 no.2
• /
• pp.449-457
• /
• 2020

The aim of this short paper is to show some rigidity results for the actions of certain finitely presented groups by homeomorphisms. As an interesting and special case, we show that the actions of Higman-Thompson groups by homeomorphisms on a cohomology manifold with a non-zero Euler characteristic should be trivial. This is related to the wellknown Zimmer program and shows that the actions by homeomorphism could be very much different from those by diffeomorphisms.

• International Journal of Advanced Culture Technology
• /
• v.6 no.4
• /
• pp.131-142
• /
• 2018

This research examines the impact of teachers' self-evaluation on their classroom interactions with students. Changes in class behavior were analyzed by following two experienced middle school teachers for one semester of self-evaluation, comparing their classes at the beginning and end of the semester. A qualitative research method was adopted to take, a deeper look at the effect of changes in the teachers' in class actions. Both of the teachers reported positive effects of implementing self-evaluation on their teaching pedagogy, focusing specifically on their interactions with students when asking question and giving feedback. By the end of semester, they were asking broader questions that encouraged their students to engage in deeper thought and, when giving feedback, the class atmosphere was much brighter with better communication due to the positive reinforcement provided. This research supports research into ways to enhance teachers' expertise and improve their teaching via self-evaluation, centering on teachers' actions in the classroom.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.190-194
• /
• 1998

In this paper, we introduce the micro robot soccer playing system as a standard test bench for the study on the multiple agent system. Our method is based on following viewpoints. They are (1) any complex behavior such as cooperation among agents must be completed by sequential basic actions of concerned agents. (2) those basic actions can be well defined, but (3) how to organize those actions in current time point so as to result in a new stale beneficial to the end aim ought to be achieved by a kind of self-learning self-organization strategy.

• Journal of the Korean Mathematical Society
• /
• v.41 no.6
• /
• pp.1101-1114
• /
• 2004

We generalize a result of Dror Farjoun and Zabrodsky on the relationship between fixed point sets and homotopy fixed point sets, which is related to the generalized Sullivan Conjecture. As an application, we discuss extension problems considering actions on homogeneous spaces of p-compact groups.

• Biomolecules & Therapeutics
• /
• v.16 no.2
• /
• pp.69-76
• /
• 2008

Lysophosphatidylcholine (LPC) is an endogenous phospholipid. LPC has various stimulating or modulating activities on immune cells, including lymphocytes, monocytes/macrophages and neutrophils. Studies generally revealed pro-inflammatory activities of LPC, but accumulating evidence indicates that LPC has also anti-inflammatory actions. Here we summarize immunomodulatory actions of LPC.

• Journal of muscle and joint health
• /
• v.22 no.1
• /
• pp.40-47
• /
• 2015

Purpose: The purpose of this study was to identify factors influencing on performance of preventive actions to be exposed to infection in emergency nurses. Methods: Participants were 200 emergency nurses working in a regional emergency medical center, 4 local emergency medical centers, and 5 local emergency medical facilities in B city. The data were analyzed with descriptive statistics, independent t-test, ANOVA, Scheff$\acute{e}$'s test, Pearson's correlation coefficients, and stepwise multiple regression analysis using SPSS/WIN 21.0 programs. Results: There was no difference in performance of preventive actions to be exposed to infection by socio-demographic and job-related characteristics. The results of stepwise multiple regression analysis showed that levels of perception of preventive actions to be exposed to infection (${\beta}$=.40, p<.001) and protective environment on exposure to infection (${\beta}$=.22, p<.001) were significantly associated with performance of preventive actions, explaining 26.3% of the variance. Conclusion: In conclusion, improving performance of preventive actions to be exposed to infection is important to protect emergency nurses from exposure to infection. Thus, efforts to enhance protective environment on exposure to infection and to improve perceptions of preventive actions to be exposed to infection are necessary to improve the performance of preventive actions in emergency nurses.

• Wind and Structures
• /
• v.37 no.2
• /
• pp.133-151
• /
• 2023

This paper first provides a wide overview about the design codes and standards covering the use of Computational Wind Engineering / Computational Fluid Dynamics (CWE/CFD) for wind-sensitive structures and built environment. Second, the paper sets out the basic assumptions and underlying concepts of the new Annex T "Simulations by Computational Fluid Dynamics (CFD/CWE)" of the revised version "Guide for the assessment of wind actions and effects on structures" issued by the Advisory Committee on Technical Recommendations for Constructions of the Italian National Research Council in February 2019 and drafted by the members of the Special Interest Group on Computational Wind Engineering of the Italian Association for Wind Engineering (ANIV-CWE). The same group is currently advising UNI CT021/SC1 in supporting the drafting of the new Annex K - "Derivation of design parameters from wind tunnel tests and numerical simulations" of the revised Eurocode 1: Actions on structures - Part 1-4: General actions - Wind actions. Finally, the paper outlines the subjects most open to development at the technical and applicative level.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.426-432
• /
• 2022

HVAC systems play a critical role in reducing energy consumption in buildings. Integrating occupants' thermal comfort evaluation into HVAC control strategies is believed to reduce building energy consumption while minimizing their thermal discomfort. Advanced technologies, such as visual sensors and deep learning, enable the recognition of occupants' discomfort-related actions, thus making it possible to estimate their thermal discomfort. Unfortunately, it remains unclear how accurate a deep learning-based classifier is to recognize occupants' discomfort-related actions in a working environment. Therefore, this research evaluates the classification performance of occupants' discomfort-related actions while sitting at a computer desk. To achieve this objective, this study collected RGB video data on nine college students' cold discomfort-related actions and then trained a deep learning-based classifier using the collected data. The classification results are threefold. First, the trained classifier has an average accuracy of 93.9% for classifying six cold discomfort-related actions. Second, each discomfort-related action is recognized with more than 85% accuracy. Third, classification errors are mostly observed among similar discomfort-related actions. These results indicate that using human action data will enable facility managers to estimate occupants' thermal discomfort and, in turn, adjust the operational settings of HVAC systems to improve the energy efficiency of buildings in conjunction with their thermal comfort levels.