• Korean Medical Education Review
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• v.25 no.2
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• pp.102-108
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• 2023

This study shares details on the operating process and results of the cohort of students and graduates that was designed and implemented at Konyang University College of Medicine in Daejeon and discusses future directions for cohort establishment and improvement. First, Konyang University College of Medicine established the necessity and defined the purpose of cohort design and implementation. A task force was formed to establish guidelines for analysis targets, procedures, reports, and data management, and cohort operation was classified as a quality control activity. Data were collected through surveys of current students and graduates, and data generated during the curriculum were collected, analyzed, and reported every 2 years. The cohort data collection and analysis methods are designed by the Department of Medical Education, and data collection is carried out by the administrative team and each committee. Data management and analysis are handled by the Center for Medical Education Support, and analysis and reporting are conducted by the Department of Medical Education. Various members of the medical school are working to collect and analyze data, report findings, provide feedback, and improve. In the future, we plan to advance database computerization and work toward more effective data analysis. Cohort operation should not be another burden for medical schools; instead, it is hoped that operating cohorts will be a meaningful activity to increase the effectiveness of medical education and help in the operation and policy decisions of medical schools.

• The Research Journal of the Costume Culture
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• v.28 no.4
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• pp.492-507
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• 2020

This study aims to develop fashion designs that combine atlas fabric with the characteristics of Uygur costume to modernize the costume of the Xinjiang Uygur. Research contents and methods are as follows. First, based on previous studies, research analysis was conducted on the cultural background, clothing characteristics, and material of Uygur clothing. Second, based on such research contents, designs combining the characteristics of Uygur costume and atlas fabric were presented. Third, to analyze the utilization of atlas fabric and examine fabric characteristics, material was gathered from collections on domestic and foreign web sites. Through field explorations of local museums in the Xinjiang area, minority group culture was observed in more detail. Based on collection of traditional clothing and analysis of its characteristics, fashion designs that apply contemporary trends were developed. General silhouettes without any restrictions to the waist and decorations made using embroidery were often used. Atlas silk, developed in China using Ikat weaving methods, is an important traditional clothing fabric of the minority group Xinjiang. Based on such data collection analysis, the produced works highlighted traditional ethnic characteristics by extracting classical patterns of atlas fabric, modifying or partially expanding them, combining them with hand knitting, and adding contemporary sensations, thus providing confirmations of the possibility of popularizing classic patterns in more practical manners.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.39-46
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• 2012

In this paper, for the cloud system by explaining how the forensic aspects of the investigation. Smartphone Growth Entering a variety of applications were developed which cloud systems of personal information and information assets sharing applications as during incidents on the case evidence collection, an important factor, whereas such systematic investigative methods, born in the course of my investigation of the can be confusing. This paper on the forensic aspects of the cloud system by proposing a crime scene investigation procedures, investigative support, and aiding in the systematic collection of data to support evidence.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2222-2240
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• 2023

Brand fandom refers to a collection of consumers with strong emotions toward a brand. Studying the dynamics of brand fandom can help brands understand which services or strategies influence their consumers to become a part of brand fandom. However, existing literature on fandom in the last three decades has mainly used qualitative methods, and there is still a lack of research on fandom using quantitative methods. Specifically, previous studies lack a framework for locating fandoms from online textual data and analyzing their dynamics. This study proposes a framework for exploring brand fandom dynamics based on online textual data. This framework consists of four phases based on the design thinking model: Preparing Data, Defining Fandom Categories, Generating Fandom Dynamics, and Analyzing Fandom Dynamics. This framework uses techniques such as social network analysis and process mining, combined with brand personality theory. We demonstrate the applicability of this framework using case studies of two Korean home appliance brands. The dataset contains 14,593 posts by consumers in 374 online communities. The results show that the proposed framework can analyze brand fandom dynamics using textual customer data. Our study contributes to the interdisciplinary research at the intersection of data-driven service design and consumer culture quantification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.943-961
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• 2020

With the advent of IoT technology and Big Data computing, the importance of WSNs (Wireless Sensor Networks) has been on the rise. For energy-efficient and collection-efficient delivery of any sensed data, lots of novel wireless medium access control (MAC) protocols have been proposed and these MAC schemes are the basis of many IoT systems that leads the upcoming fourth industrial revolution. WSNs play a very important role in collecting Big Data from various IoT sensors. Also, due to the limited amount of battery driving the sensors, energy-saving MAC technologies have been recently studied. In addition, as new IoT technologies for Big Data computing emerge to meet different needs, both sensors and sinks need to be mobile. To guarantee stability of WSNs with dynamic topologies as well as frequent physical changes, the existing MAC schemes must be tuned for better adapting to the new WSN environment which includes energy-efficiency and collection-efficiency of sensors, coverage of WSNs and data collecting methods of sinks. To address these issues, in this paper, a self-organization scheme for mobile sensor networks with mobile multiple sinks has been proposed and verified to adapt both mobile sensors and multiple sinks to 3-dimensional group management MAC protocol. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of the various usage cases. Therefore, the proposed self-organization scheme might be adaptable for various computing and networking environments with big data.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.395-402
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• 2022

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.123-133
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• 2008

Information collection systems and applications in a ubiquitous environment has emerged as a leading issue in transportation and logistics. A productive application example is a traffic information collection system based on probe vehicles and wireless communication technology. Estimation of hourly OD pairs using probe OD data is a possible target. Since probe OD data consists of sample OD pairs, which vary over time and space, computation of sample rates of OD pairs and expansion of sample OD pairs into static OD pairs is required. In this paper, the authors proposed a method to estimate sample OD data with probe data in Jeju City and expand those into static OD data. Mean absolute percentage difference (MAPD) error between observed traffic volume and assigned traffic volume was about 22.9%. After removing abnormal data, MAPD error improved to 17.6%. Development of static OD estimation methods using probe vehicle data in a real environment is considered the main contribution of this paper.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.2
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• pp.21-58
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• 2009

The Purpose of this study is working out of the scientific-theoretical and practical recommendations directed on perfection of strategic planning of development of the enterprises of mining and gold mining branch. The methodological basis of research is based on the economic theory developed by a domestic and foreign science. At processing, generalisation and a writing of materials of the master's thesis following methods were applied: - supervision, - comparison, - the analysis and synthesis, - methods of an induction and deduction, - statistical groupings, - average and relative sizes, - the system approach. Finally, the theoretical and practical importance of this research consists that results of research will allow generating a basis of statement of effective system of strategic planning of a long-term sustainable development of the gold mining enterprises reducing risk of acceptance of inefficient strategic decisions. I would like to express many thanks to the NGO "Semey- My Home" and "EastGeoResources" LLP for their help and support in providing the data collection and data analysis stages of my research from 2006.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.785-792
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• 2021

Since the Fourth Industrial Revolution, various changes have occurred in society as a whole due to advance in technologies such as artificial intelligence and big data. The amount of data that can be collect in the process of applying important technologies tends to increase rapidly. Especially in academia, existing generated literature data is analyzed in order to grasp research trends, and analysis of these literature organizes the research flow and organizes some research methodologies and themes, or by grasping the subjects that are currently being talked about in academia, we are making a lot of contributions to setting the direction of future research. However, it is difficult to access whether data collection is necessary for the analysis of document data without the expertise of ordinary programs. In this paper, propose a text mining-based topic modeling Web application model. Even if you lack specialized knowledge about data analysis methods through the proposed model, you can perform various tasks such as collecting, storing, and text-analyzing research papers, and researchers can analyze previous research and research trends. It is expect that the time and effort required for data analysis can be reduce order to understand.

• Journal of Korean Academy of Nursing
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• v.26 no.2
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• pp.497-506
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• 1996

Gradually, there has been increase in the use of qualitative research methods in nursing research. Nursing scholars are using qualitative research methods to explore the essence of nursing and discover its meaning. However, there has been lack of standards for evaluating qualitative nursing research. Often nursing researchers are applying quantitative research evaluation standards to qualitative nursing research. Thus, there has not been any notable qualitative research done to date. In order to improve the quality of nursing research done to discover new knowledge for the nursing, ＆ for development of nursing theory, criteria for critiquing qualitative research should be established. Therefore, this researcher introduced standards as criteria for critiquing qualitative research which are based on literature reviews and re search experiences. The suggested criteria are developed several question's as follows : 1) description of the research phenomena, 2) significance, 3) research purpose, 4) research question, 5) assumptions, 6) researcher's abilities, 7) selection of research samples, 8) data collection, 9) human subjects, 10) data analysis, 11) description of researcher's results, 12) literature review. Follow-up of concrete questions for each of the criterias have been developed.