• International Journal of Advanced Culture Technology
• /
• v.11 no.4
• /
• pp.169-176
• /
• 2023

This study aims to assess the current status of career education at C University and to gather foundational data for developing a step-by-step career education curriculum and an integrated roadmap for curriculum and extracurricular career education. This research involves a comparative analysis of C University's enrolled students and external university students through a survey using the [University Career Exploration Model]. Data collection took place over one month in October 2023, and statistical analysis was conducted using the SPSS Statistics 25.0 program. The survey results enabled a comparative analysis of the career exploration processes and levels between enrolled students at C University and external university students. The proportion of enrolled students at C University responding positively to the career exploration process and level was high. Through this study, a better understanding of the career exploration processes and levels of university students was achieved. It is deemed necessary to conduct systematic research for continuous, tailored integration of curriculum and extracurricular career education at the university level.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.25 no.3
• /
• pp.586-597
• /
• 2001

EThe purpose of this study was to investigate the relationships of consumers psychological characteristics, store types and impulse buying behaviors of apparels. We collected data from 469 consumers of women college student living in Pusan and analysed by factor analysis, frequency analysis, correlation analysis, t-test and $\chi$$^2$-test. The results were as follows: First, The sensation seeking tendency consisted of the Change seeking, Risk seeking, Artistic seeking, Curiosity seeking and Unusual seeking. The exploratory behavior of apparels were divided into six factors; Particularity exploration, Innovation exploration, Store exploration, Brand royalty exploration, interpersonal exploration and brand-seeking exploration. Second, In comparison with the unimpulse-buying group, the impulse-buying group intended more then Change seeking, when apparel explored, Particularity exploration, Innovation exploration and Brand exploration. Impulse-buying group preferred the department store, unimpulse-buying group did the specialty store.

• Journal of Practical Engineering Education
• /
• v.15 no.2
• /
• pp.401-408
• /
• 2023

In this study, a career exploration program was developed for athletic students. Therefore, existing research on career exploration for athletics was analyzed, requirements were identified, and a learning plan was designed. Based on this, a step-by-step educational program was developed. In addition, since research on career exploration for athletic students was not active in previous studies, 'problem definition' - 'data collection' - 'data preprocessing' - 'data analysis' by referring to existing career exploration studies that were studied in the school field. - 'Data visualization' - 'Simulation analysis' were divided into stages to conduct the study. Through this study, it is expected that research on vocational education for athletic students will be more active.

• Publications of The Korean Astronomical Society
• /
• v.32 no.1
• /
• pp.209-211
• /
• 2017

We performed Principle Component Analysis (PCA) over 264 galaxies in the IRAS Revised Bright Galaxy Sample (Sanders et al., 2003) using 12, 25, 60 and $100{\mu}m$ flux data observed by IRAS and 9, 18, 65, 90 and $140{\mu}m$ flux data observed by AKARI. We found that (i)the first principle component was largely contributed by infrared to visible flux ratio, (ii)the second principal component was largely contributed by the flux ratio between IRAS and AKARI, (iii)the third principle component was largely contributed by infrared colors.

• Genomics & Informatics
• /
• v.1 no.2
• /
• pp.65-74
• /
• 2003

Data mining differs primarily from traditional data analysis on an important dimension, namely the scale of the data. That is the reason why not only statistical but also computer science principles are needed to extract information from large data sets. In this paper we briefly review data mining, its characteristics, typical data mining algorithms, and potential and ongoing applications of data mining at biopharmaceutical industries. The distinguishing characteristics of data mining lie in its understandability, scalability, its problem driven nature, and its analysis of retrospective or observational data in contrast to experimentally designed data. At a high level one can identify three types of problems for which data mining is useful: description, prediction and search. Brief review of data mining algorithms include decision trees and rules, nonlinear classification methods, memory-based methods, model-based clustering, and graphical dependency models. Application areas covered are discovery compound libraries, clinical trial and disease management data, genomics and proteomics, structural databases for candidate drug compounds, and other applications of pharmaceutical relevance.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.11
• /
• pp.77-88
• /
• 2015

This study attempts to investigate the effect of team diversity on individual creativity and team members' creative activities such as exploration and exploitation. We have garnered 40 team data from 249 respondents who have been participating in the team learning activities during semester in a private university. They were asked by instructor to show their creativity, and exploration and exploitation activities. The 40 teams were made up of team diversity factors such as study hour and leisure activity. We used a multilevel analysis to analyze the effects of team diversity factors on team member's creativity, and exploration and exploitation. Results showed that in general, team diversity factors like study hour and leisure activities have significant effects on the individual creativity, and exploration and exploitation. Practical implications represent that teams need to be organized considering the team diversity factors in order to improve team member's creativity, and their exploration and exploitation activities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.2
• /
• pp.109-118
• /
• 2022

GPR (Ground Penetrating Radar), developed as a technology for geotechnical investigations such as sinkhole exploration, was used limitedly as a method to resolve undetectable lines in underground facility exploration. To improve the accuracy of underground facility data, the government made it possible to explore underground facilities using a non-metallic pipeline probe from July 2022. However, GPR has a problem in that the exploration rate is lowered in the soil with high moisture content, such as soft soil, such as clay layer, and there is a lot of variation in long-term accuracy. In this study, as a way to improve the accuracy of exploration considering the characteristics of GPR and the environment of underground facilities, we propose a GPR exploration method for underground facilities using permittivity constant correction and pattern analysis of GPR image data. Through this study, the accuracy of underground facility exploration and high reproducibility were derived as a result of field verification applying GPR frequency band and heterogeneous GPR.

• Geophysics and Geophysical Exploration
• /
• v.17 no.4
• /
• pp.242-246
• /
• 2014

Spectral induced polarization (SIP) is a useful technique, which uses electrochemical properties, for exploration of metallic sulfide minerals. Equivalent circuit analysis is commonly conducted to calculate IP parameters from SIP data. An equivalent circuit model, which indicates the SIP response of rock, has a non-uniqueness problem. For this reason, it is very important to select the proper model for accurate analysis. Thus, this study focused on suggesting a new model, which suitable for the analysis of an anomalous SIP response, such as ore. A suitability of the new model was verified by comparing it with the existing Dias model and Cole-Cole models. Analysis errors were represented as a normalized root mean square error (NRMSE). The analysis result using the Dias model was the NRMSE of 10.50% and was the NRMSE using the Cole-Cole model of 17.03%. Howerver, because the NRMSE of the new model is 0.87%, it is considered that the new model is more useful for analyzing the anomalous SIP data than other models.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2011.10a
• /
• pp.31-32
• /
• 2011

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.662-663
• /
• 2004

In general, mineral resources prospect is performed in several methods including geological survey, geological structure analysis, geochemical exploration, airborne geophysical exploration and remote sensing, but data collected through these methods are usually not integrated for analysis but used separately. Therefore we compared various data integration techniques and generated final mineral resources potentiality map.