• Safety and Health at Work
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• v.11 no.1
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• pp.1-9
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• 2020

Background: As the impact of climate change intensifies, exposure to heat stress will grow, leading to a loss of work capacity for vulnerable occupations and affecting individual labor decisions. This study estimates the future work capacity under the Representative Concentration Pathways 8.5 scenario and discusses its regional impacts on the occupational structure in the Republic of Korea. Methods: The data utilized for this study constitute the local wet bulb globe temperature from the Korea Meteorological Administration and information from the Korean Working Condition Survey from the Occupational Safety and Health Research Institute of Korea. Using these data, we classify the occupations vulnerable to heat stress and estimate future changes in work capacity at the local scale, considering the occupational structure. We then identify the spatial cluster of diminishing work capacity using exploratory spatial data analysis. Results: Our findings indicate that 52 occupations are at risk of heat stress, including machine operators and elementary laborers working in the construction, welding, metal, and mining industries. Moreover, spatial clusters with diminished work capacity appear in southwest Korea. Conclusion: Although previous studies investigated the work capacity associated with heat stress in terms of climatic impact, this study quantifies the local impacts due to the global risk of climate change. The results suggest the need for mainstreaming an adaptation policy related to work capacity in regional development strategies.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.17-24
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• 2008

The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3112-3127
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• 2018

Since time series clustering is performed without prior information, it is used for exploratory data analysis. In particular, clusters of time series with similar shapes can be used in various fields, such as business, medicine, finance, and communications. However, existing time series clustering algorithms have a problem in that time series with different shapes are included in the clusters. The reason for such a problem is that the existing algorithms do not consider the limitations on the size of the generated clusters, and use a dimension reduction method in which the information loss is large. In this paper, we propose a method to alleviate the disadvantages of existing methods and to find a better quality of cluster containing similarly shaped time series. In the data preprocessing step, we normalize the time series using z-transformation. Then, we use piecewise aggregate approximation (PAA) to reduce the dimension of the time series. In the clustering step, we use density-based spatial clustering of applications with noise (DBSCAN) to create a precluster. We then use a modified K-means algorithm to refine the preclusters containing differently shaped time series into subclusters containing only similarly shaped time series. In our experiments, our method showed better results than the existing method.

• Parasites, Hosts and Diseases
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• v.60 no.2
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• pp.97-107
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• 2022

This study was done to provide an overview of the latest trichomoniasis status in Korea by finding disease clusters and analyzing temporal trends during 2012-2020. Data were obtained from the Health Insurance Review & Assessment Service (HIRA) of Korea. SaTScan and Joinpoint programs were used for statistical analyses. Gyeonggi-do had the highest average population and highest number of cases. The high incidence of T. vaginalis infections were observed among women aged 40-49 and 30-39 years (33,830/year and 33,179/year, respectively). Similarly, the 40-49 and 30-39 age group in men showed the highest average cases (1,319/year and 1,282/year, respectively). Jeollabuk-do was the most likely cluster, followed by Busan/Gyeongsangnam-do/Ulsan/Daegu and Jeju-do and Gwangju. Urban and rural differences were prominent. Trichomoniasis has decreased significantly in most clusters, except for Incheon. Trichomoniasis was decreasing in women recently after peaking around 2014. Men showed different trends according to age. Trichomoniasis was increasing in the 10-39 age groups, but decreasing in the 40-59 age groups. This study might provide an analytic basis for future health measures, policy-makers, and health authorities in developing effective system for prevention of trichomoniasis.

• Journal of IKEEE
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• v.27 no.4
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• pp.439-449
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• 2023

In an era marked by the increasing use of drones and the growing demand for indoor surveillance, the development of a robust application for detecting and tracking both drones and humans within indoor spaces becomes imperative. This study presents an innovative application that uses FMCW radar to detect human and drone motions from the cloud point. At the outset, the DBSCAN (Density-based Spatial Clustering of Applications with Noise) algorithm is utilized to categorize cloud points into distinct groups, each representing the objects present in the tracking area. Notably, this algorithm demonstrates remarkable efficiency, particularly in clustering drone point clouds, achieving an impressive accuracy of up to 92.8%. Subsequently, the clusters are discerned and classified into either humans or drones by employing a deep learning model. A trio of models, including Deep Neural Network (DNN), Residual Network (ResNet), and Long Short-Term Memory (LSTM), are applied, and the outcomes reveal that the ResNet model achieves the highest accuracy. It attains an impressive 98.62% accuracy for identifying drone clusters and a noteworthy 96.75% accuracy for human clusters.

• Journal of The Korean Astronomical Society
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• v.35 no.2
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• pp.87-95
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• 2002

We have conducted VI CCD photometry of the open cluster NGC 6819 in order to understand the effects of dynamical evolution in old open clusters. Our photometry covers 18' $\times$ 18' on the sky, centered on the cluster, which seems to cover the whole cluster field. Our photometry reaches down to V $\approx$ 20.5, which allows us to analyze the luminosity function and spatial distribution of stars brighter than Mv $\approx$ 8.5. There is a clear evidence for mass segregation in NGC 6819, i.e., the giants and upper main-sequence stars are concentrated in the inner regions, whereas the lower main-sequence stars distribute almost uniformly throughout the cluster. The luminosity function of the main-sequence stars of NGC 6819 is almost flat. The flat luminosity function indicates that a large number of low mass stars has escaped from the cluster unless its initial mass function is much different from the Salpeter type (${\phi}(m){\propto} m^{-(1+x)},x = 1.35$).

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.30.2-30.2
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• 2015

Abell 2744 is a giant merging cluster, called the Pandora's Cluster, at the redshift of z=0.308 (corresponding to a distance of 1270 Mpc). Taking the advantage of the deep high resolution images in the Hubble Frontier Field program, we study the properties of compact stellar systems including globular clusters and ultracompact dwarfs (UCDs) as well as dwarf galaxies in this cluster. We find a rich population of globular clusters and UCDs in Abell 2744. The spatial distribution of these objects is consistent with the mass map derived from lensing analysis, while showing a significant offset from the X-ray map of hot gas. The faint end of the luminosity function of the galaxies in the red sequence is fit by a flat slope, showing no faint upturn. We discuss these finding in relation with the origin of UCDs, formation of red sequence dwarf galaxies, and formation of the Pandora's cluster.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.275-278
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• 2015

We studied a cluster family in the northern part of the Carina Nebula (NGC 3372) a group of clusters near NGC 3324 (Tr 15, NGC 3293, Loden 165, Loden 153 and IC 2581). We used data from UCAC4 to determine the cluster's membership and the near infrared CMDs of each cluster. We analyzed the spatial density and elongation as a function of radius for each cluster and found a possible interaction between NGC 3293 and Loden153. However, the shape distortion of NGC 3324 cannot be evaluated because of the inhomogenity in the coverage of UCAC4 in the east part of NGC 3324.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.69.1-69.1
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• 2012

We present a comprehensive study of star-forming regions and young star clusters in M33. We use GALEX far-UV and near-UV imaging to detect these young stellar populations tracing recent star formation across the disk of M33. The GALEX imaging, combining deep sensitivity and entire coverage of the galaxy, provides a complete view of the recent star formation in M33 and its variation with environment throughout the galaxy. We discuss variation of various properties (e.g., age, mass, spatial distribution) of star-forming regions and young star clusters in M33 which allow to provide constraints of recent star formation history of this galaxy.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.47.2-47.2
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• 2019

We present a kinematic study of the two young OB associations Cygnus OB2 and Carina OB1 using the recently released Gaia astrometric data. The unimodal distributions of parallaxes of stars indicate that these associations are real stellar systems, rather than line-of-sight coincidences. The associations are found to comprise dense star clusters and a sparse halo which have different proper motions. Clusters have small spatial sizes with small dispersions in proper motion, while the haloes extending to tens of parsecs have a large dispersion in proper motion. We speculate that this aspect is related to that found in molecular clouds, the so-called "line width-size" relation. In this talk, the formation process of these associations is discussed, based on our findings.