• Journal of the Korean Society for information Management
• /
• v.37 no.3
• /
• pp.77-106
• /
• 2020

In this study, we proposed a method to systematically manage research data in the field of condensed matter physics, which is the most active and interdisciplinary field. In the course of the research, a questionnaire was conducted for researchers in the field of condensed matter physics. The questionnaire was constructed based on the research data management tool Data Asset Framework (DAF) and the FAIR principle for data sharing and reuse. The current status of research data management in the field of aggregated material physics was collected from 14 researchers. The collected data consisted of data on the characteristics and basic information of researchers who answered the questionnaire, data preservation and management, and data sharing and access. By analyzing the collected questionnaire results, nine problems were drawn about the characteristics of research data in the field of aggregate material physics, data collection and production, data preservation and management, data sharing and access. In this study, suggestions were made to improve the problems derived from each aspect.

• Journal of Korea Multimedia Society
• /
• v.14 no.3
• /
• pp.392-402
• /
• 2011

Snow fall and icing on traffic roads in the winter season cause not only inconvenience but unexpected traffic accidents, so the proper measures are needed. The existing road information system is being installed for steep slope roads in mountain areas, however, it is not widely adopted because it is too expensive. In this paper, a novel and cost-effective road weather information system especially for snow fall and icing on roads is proposed. The system consists of digital temperature and relative humidity sensor, infrared temperature sensor, ultrasonic sensor, CMOS camera, and two types of control/communication board for ubiquitous sensor network to send the data to server. The server program including the decision making method with received data is also described. Experimental results are provided to prove the feasibility of the proposed system.

• Journal of Korean Society of Archives and Records Management
• /
• v.17 no.4
• /
• pp.127-154
• /
• 2017

Large-scale and complex disasters have frequently occurred all over the world recently, and they are repeated every year. Accordingly, the need for the systematic management and utilization of raw-data and processing information in the past has increased. For this purpose, this study proposed a construction strategy for disaster and safety record information resources archives based on automatic acquisition, which can be used as a hub for disaster and safety information. Based on local and foreign case studies, several consideration factors for building the archives are determined. Finally, this study proposed four steps for constructing the archives. These are as follows: 1) complete enumeration survey of the disaster and safety record information resources, 2) automatic acquisition possibility study, 3) selection of the resources for preservation, and 4) automatic acquisition of metadata. The construction of the archives proposed in this study will facilitate integrated management, sharing, and use of scattered information resources on disaster and safety.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.46 no.9
• /
• pp.767-773
• /
• 2018

In many cases, modern aircraft are equipped with data acquisition system which checks the structural integrity of the aircraft. The analysis of the vibration data collected with the system is generally performed in dependence on a skilled expert who is familiar with aircraft design. Therefore, it is difficult to provide a representative and objective defect identification standard for general users. In this paper, we shows that it is possible to identify the type of maneuvers and faults by using the Principal Component Analysis(PCA) method in the vast vibration data collected during aircraft operation without using the existing aircraft design analysis. We classified the ROK Army aircraft vibration data for maneuvers and faults types, and applied the PCA to the classified data. Our result shows that it is possible to develop an objective maneuver/fault identification method without design analysis for general users.

• The Korean Journal of Archival Studies
• /
• no.20
• /
• pp.115-150
• /
• 2009

Theater is a performing art with a volatile feature which exists when it is performed on the stage by actors and disappears when it is finished. Due to its intangible characteristic It is not only impossible to just hand it down but also there is a high possibility that materials which have been produced during the preparations of performance might be lost If it was not been properly taken care. The study which has been conducted from the existing such a problem, understand produceable records, the point where the records can be produced and the main body who is in charge of the production process by analysing performing process of theater and also propose the general method of documentation of theater by introducing the method of collecting each records. Such an introduction of method would help to progress acquisition activity by setting-up documentation planning at the stage of planning theater beforehand, rather than just help to gather the corresponding records after the performance is finished.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1904-1913
• /
• 2021

With the proliferation of smart phones and the development of IoT technology, it has become possible to collect personal data for public purposes. However, users are afraid of voluntarily providing their private data due to privacy issues. To remedy this problem, mainly three techniques have been studied: data disturbance, traditional encryption, and homomorphic encryption. In this work, we perform simulations to compare them in terms of accuracy, message length, and computation delay. Experiment results show that the data disturbance method is fast and inaccurate while the traditional encryption method is accurate and slow. Similar to traditional encryption algorithms, the homomorphic encryption algorithm is relatively effective in privacy preserving because it allows computing encrypted data without decryption, but it requires high computation costs as well. However, its main cost, arithmetic operations, can be processed in parallel. Also, data analysis using the homomorphic encryption needs to do decryption only once at any number of data.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.1
• /
• pp.453-458
• /
• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.6
• /
• pp.519-525
• /
• 2018

The purpose of this study was to identify the incidence of neutropenia in patients with breast cancer who received chemotherapy and to identify the differences in incidence according to influential factors. We analyzed the medical records of 353 breast cancer patients who received chemotherapy at university hospital in Seoul, Korea from January 2010 to March 2016. The collected data were analyzed by descriptive statistics, $X^2-test$, and logistic regression analysis using SPSS 20.0. Among the 353 subjects, 33.1% had neutropenia, and the factors that showed significant difference according to neutropenia were exercise performance, RT status, and regimen. The results of this study suggest that it is important to predict the prevalence of neutropenia in breast cancer patients receiving chemotherapy and to provide appropriate education and nursing intervention.

• Journal of Convergence for Information Technology
• /
• v.10 no.7
• /
• pp.84-97
• /
• 2020

This pilot study evaluated the reach and efficacy of nurse training program to provide palliative care to patients with advanced chronic diseases. A mixed method was used (an one-group pre-post research design and a group interview). To examine the changes in knowledge, attitude and self-efficacy, paired t-test were used with SPSS 21.0. To obtain pivoting information in real settings, a content analysis was conducted in the data obtaining from a group interview. There were significant improvements on knowledge and self-efficacy scores after the program. Additionally, high retention rate and program satisfaction were found in the participants while recruitment strategies, especially nurses working for tertiary hospitals, need to be modified in future research. A full-fledged research is warranted to find effective strategies to implement and disseminate the program for nurses working in diverse settings.

• Journal of Digital Convergence
• /
• v.18 no.8
• /
• pp.231-242
• /
• 2020

The thesis presents a system that continuously collects the human body's physiological vital information at rest with sensors and ICT information technology and predicts diabetes using the collected information. it shows the artificial neural network machine learning method and essential basic variable values. The study method analyzed the correlation between heart rate measurements of BCG and ECG sensors in 20 DM- and 15 DM+ subjects. Artificial Neural Network (ANN) machine learning program was used to predictability of diabetes. The input variables are time domain information of HRV, heart rate, heart rate variability, respiration rate, stroke volume, minimum blood pressure, highest blood pressure, age, and sex. ANN machine learning prediction accuracy is 99.53%. Thesis needs continuous research such as diabetic prediction model by BMI information, predicting cardiac dysfunction, and sleep disorder analysis model using ANN machine learning.