• The Bulletin of The Korean Astronomical Society
• /
• v.44 no.1
• /
• pp.47.3-47.3
• /
• 2019

We discovered 722 open clusters within 1 kpc using Gaia DR2 data. These clusters are detected in the proper motion space and confirmed on the spatial distribution with parallax information. We divided the 3628 regions and visually searched using python program. Among 722 open clusters, 430 clusters are previously unknown clusters. Catalogue of discovered clusters is unloaded on the online catalogue at https://radio.kasi.re.kr/project/shlee/. Owing to the good membership criteria, we could see the halo structure of the clusters. In that reason, the average size of the discovered cluster is about 9 times than that of previously known clusters.

• Journal of Platform Technology
• /
• v.10 no.3
• /
• pp.3-10
• /
• 2022

The effectiveness of an innovative skin treatment system that delivers an anti-aging solution deep into the skin without invasiveness and pain using a non-invasive air technology was investigated. In addition, an effective change using a non-invasive technique for delivering a solution for skin improvement was confirmed. The equipment named Cellre Jet is an effective skin care and drug delivery equipment that instantly opens the skin epidermis by using a maximum output pressure of 6 bars and high-pressure purified oxygen of 75-90% purity to deliver various nano-sized vital substances deep into the skin, and it uses the method of precisely controlling the equipment through an 8-inch digital touch display to accurately dispense the prescribed dosage. In this study, changes in skin condition were analyzed using this equipment and nano ampoules on subjects with actual skin problems through a related comparison and effectiveness judgment program. Through this study, skin care and drug delivery are possible, which will contribute to verifying the effectiveness of this non-invasive drug delivery equipment in the future, and is expected to establish the systematic effect in observing and studying changes in the skin.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.07a
• /
• pp.133-134
• /
• 2022

With the advent of PyScript, there are more and more topics in practice. However, the official guideline has not provided a detailed description. This paper investigates the practical application about PyScript. The research results show that the current functions in PyScript cannot be well handled in web pages, and even cannot use the advantage model of Python, which is not suitable for practical application in the short term. However, it may be widely used in web development in the future since writing functions through Wasm can improve the efficiency of program execution.

• Current Optics and Photonics
• /
• v.7 no.6
• /
• pp.683-691
• /
• 2023

A typical terahertz time-domain spectroscopy system requires large, expensive, and heavy hardware such as a lock-in amplifier and a function generator. In this study, we replaced the lock-in amplifier and the function generator with a single sound card built into a typical desktop computer to significantly reduce the system size, weight, and cost. The sound card serves two purposes: 1 kHz chopping signal generation and raw data acquisition. A unique software lock-in (Python coding program to eliminate noise from raw data) method was developed and successfully extracted THz time-domain signals with a signal-to-noise ratio of ~40,000 (the intensity ratio between the peak and average noise levels). The built-in sound card with the software lock-in method exhibited sufficiently good performance compared with the hardware-based method.

• Journal of Korean Society for Geospatial Information Science
• /
• v.25 no.1
• /
• pp.37-46
• /
• 2017

Recently, disaster caused by social factors is frequently occurring in Korea. Prediction about what crisis could happen is difficult, raising the citizen's concern. In this study, we developed a program to acquire tweet data by applying Python language based Tweepy plug-in, regarding social disasters such as 'Nonspecific motive crimes' and 'Oxy' products. These data were used to evaluate psychological trauma and anxiety of citizens through the text clustering analysis and the opinion mining analysis of the R Studio program after natural language processing. In the analysis of the 'Oxy' case, the accident of Sewol ferry, the continual sale of Oxy products of the Oxy had the highest similarity and 'Nonspecific motive crimes', the coping measures of the government against unexpected incidents such as the 'incident' of the screen door, the accident of Sewol ferry and 'Nonspecific motive crime' due to misogyny in Busan, had the highest similarity. In addition, the average index of the Citizens sentiment score in Nonspecific motive crimes was more negative than that in the Oxy case by 11.61%p. Therefore, it is expected that the findings will be utilized to predict the mental health of citizens to prevent future accidents.

• The Bulletin of The Korean Astronomical Society
• /
• v.42 no.1
• /
• pp.33.1-33.1
• /
• 2017

Molecular clouds are the sites of stellar birth, and conditions within the clouds control the mode and tempo of star formation. In particular, turbulence largely determines the density and velocity fields, and can affect the gas kinetic temperature as it decays via shocks. However, despite its central role in star formation and many years of study, the properties of turbulence remain poorly understood. As a part of the TRAO key science program, "Mapping turbulent properties of star-forming molecular clouds down to the sonic scale (PI: Jeong-Eun Lee)", we mapped the northern region of the Orion A molecular cloud and the L1688 region of the ${\rho}$ Ophiuchus molecular cloud in 2 sets of lines (13CO 1-0/C18O 1-0 and HCN 1-0/and HCO+ 1-0) using the Taeduk Radio Astronomy Observatory (TRAO) 14-m telescope. We analyze these maps using a python package 'Turbustat', a toolkit which contains 16 different turbulent statistics. We will present the preliminary results of our TRAO observations and various turbulence statistical analyses.

• Nuclear Engineering and Technology
• /
• v.53 no.10
• /
• pp.3449-3459
• /
• 2021

With the increasing availability of high-performance computing (HPC) platforms, uncertainty quantification (UQ) and sensitivity analyses (SA) can be efficiently leveraged to optimize design parameters of complex engineering problems using modeling and simulation tools. The workflow involved in such studies heavily relies on HPC resources and hence requires pre-processing and post-processing capabilities of large amounts of data along with remote submission capabilities. The NEAMS Workbench addresses all aspects of the workflows involved in these studies by relying on a user-friendly graphical user interface and a python application program interface. This paper highlights the NEAMS Workbench capabilities by presenting a semiautomated coupling scheme between Dakota and any given package integrated with the NEAMS Workbench, yielding a simplified workflow for users. This new capability is demonstrated by running a SA of a turbulent flow in a pipe using the open-source Nek5000 CFD code. A total of 54 jobs were run on a HPC platform using the remote capabilities of the NEAMS Workbench. The results demonstrate that the semiautomated coupling scheme involving Dakota can be efficiently used for UQ and SA while keeping scripting tasks to a minimum for users. All input and output files used in this work are available in https://code.ornl.gov/neams-workbench/dakota-nek5000-study.

• Geomechanics and Engineering
• /
• v.25 no.1
• /
• pp.17-30
• /
• 2021

This paper develops a convenient approach for deterministic and probabilistic evaluations of tunnel face stability using support vector machine classifiers. The proposed method is comprised of two major steps, i.e., construction of the training dataset and determination of instance-based classifiers. In step one, the orthogonal design is utilized to produce representative samples after the ranges and levels of the factors that influence tunnel face stability are specified. The training dataset is then labeled by two-dimensional strength reduction analyses embedded within OptumG2. For any unknown instance, the second step applies the training dataset for classification, which is achieved by an ad hoc Python program. The classification of unknown samples starts with selection of instance-based training samples using the k-nearest neighbors algorithm, followed by the construction of an instance-based SVM-KNN classifier. It eventually provides labels of the unknown instances, avoiding calculate its corresponding performance function. Probabilistic evaluations are performed by Monte Carlo simulation based on the SVM-KNN classifier. The ratio of the number of unstable samples to the total number of simulated samples is computed and is taken as the failure probability, which is validated and compared with the response surface method.

• The Journal of Economics, Marketing and Management
• /
• v.10 no.6
• /
• pp.1-7
• /
• 2022

Purpose: The purpose of this study is identifying the research trends of degree papers related to the beauty industry and providing information which can contribute to the development of the domestic beauty industry and the direction of various research about beauty industry. Research design, data and methodology: This study used 154 academic papers and 189 academic papers with English abstracts out of 299 academic papers. All of these papers were found by searching for the keyword "beauty industry" in ScienceON on August 15, 2022. For the analysis, BERTopic and LDA (Latent Dirichlet Allocation) analysis were conducted using Python 3.7. Also, OLS regression analysis was conducted to understand the annual increase and decrease trend of each topic derived with trend analysis. Results: As a result of word frequency analysis, the frequency of satisfaction, management, behavior, and service was found to be high. In addition, it was found that 'service', 'satisfaction' and 'customer' were frequently associated with program and relationship in the word co-occurrence frequency analysis. As a result of topic modeling, six topics were derived: 'Beauty shop', 'Health education', 'Cosmetics', 'Customer satisfaction', 'Beauty education', and 'Beauty business'. The trend analysis result of each topic confirmed that 'Beauty education' and 'Health education' are getting more attention as time goes by. Conclusions: The future studies must resolve the extreme polarization between the structure of the small beauty industry and beauty stores. Furthermore, the researches have to direct various ways to create the performance of internal personnel. The ways to maximize product capabilities such as competitive cosmetics and brands are also needed attentions.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.44 no.5
• /
• pp.1019-1035
• /
• 2020

This study examines the millennial generation, who express themselves and share information on social media after experiencing constantly changing 'hot places' (places of interest) in contemporary cities, with the goal of analyzing space consumption behaviors. Data were collected via an Instagram crawler application developed with Python 3.4 administered to 19,262 posts using the term 'hot places' from November 1 and December 15, 2019. Issues were derived from a text mining technique using Textom 2.0; in addition, semantic network analysis using Ucinet6 and the NetDraw program were also conducted. The results are as follows. First, a frequency analysis of keywords for hot places indicated words frequently found in nouns were related to food, local names, SNS and timing. Words related to positive emotions felt in experience, and words related to behavior in hot places appeared in predicate. Based on importance, communication is the most important keyword and influenced all issues. Second, the results of visualization of semantic network analysis revealed four categories in the scope of the definition of "hot place": (1) culinary exploration, (2) atmosphere of cafés, (3) happy daily life of 'me' expressed in images, (4) emotional photos.