• Journal of the Economic Geographical Society of Korea
• /
• v.11 no.3
• /
• pp.334-349
• /
• 2008

In this study, the network formation process of personal actors in industries for the elderly was analyzed. This process is applied to the knowledge creation model of the SECI (Nonaka-Takeuchi learning cycle), that is socialization, externalization, combination, internalization. There are some kinds of opportunities to interact in these industries in the forms of field survey teams to overseas, some seminars and symposiums, many kinds of meetings, education and training programs, trade fairs and on-line forums. These palces(ba) - originating ba, interacting ba, cyber ba, exercising ba - played great roles in the formation of personal actor networks. Personal actors had opportunities to interconnect with distant actors through those places(ba). In the spatial perspective, personal actors could make face-to-face contact and build trust through temporary geographical proximity or temporary clusters with the help of personal mobility. Relations in the virtual spaces such as the Internet community did much toward building personal networks.

• Journal of the Korea Society for Simulation
• /
• v.26 no.3
• /
• pp.73-86
• /
• 2017

Environmental data plays an important role to enhance the reliability of experimental results in M&S(Modeling and Simulation). Especially in Military M&S, extreme weather events can be used for virtual training and simulation importantly. However, the environmental data is huge and it is dispersed among multiple organizations. It is difficult for M&S operators to select the date and area where the weather phenomenon occurs in the real environmental data and to acquire them. Environmental data retrieval technology based on Fuzzy criteria is one of the important technologies for developing Environmental Scenario Generator. As a result of this study, a fuzzy retrieval algorithm composed of four main parameters(RV, MF, FRA, and MRV) was presented. This study suggests that the RV can be used as 14 m/s for wind speed and 80 mm/d for precipitation to search the date of storm accompanied by high wind. The MF, the FRA, and MRV can be used sigmoid, 0.2, and 1 respectively. The algorithm proposed in this study is expected to be very useful for searching the date on which weather phenomena necessary for simulation occurred.

• Journal of the Korean Institute of Gas
• /
• v.25 no.5
• /
• pp.63-69
• /
• 2021

In this study, we established an algorithm to determine whether the work in the gas facility is a normal work or an abnormal work using the threshold of the reconstruction error of the autoencoder. This algorithm do deep learning the autoencoder only with time-series data of a normal work, and derives the optimized threshold of the reconstruction error of the normal work. We applied this algorithm to the time series data of the new work to get the reconstruction error, and then compare it with the reconstruction error threshold of the normal work to determine whether the work is normal work or abnormal work. In order to train and validate this algorithm, we defined the work in a virtual gas facility, and constructed the training data set consisting only of normal work data and the validation data set including both normal work and abnormal work data.

• Healthcare Informatics Research
• /
• v.24 no.4
• /
• pp.394-401
• /
• 2018

Objectives: Augmented reality (AR) technology has become rapidly available and is suitable for various medical applications since it can provide effective visualization of intricate anatomical structures inside the human body. This paper describes the procedure to develop an AR app with Unity3D and Vuforia software development kit and publish it to a smartphone for the localization of critical tissues or organs that cannot be seen easily by the naked eye during surgery. Methods: In this study, Vuforia version 6.5 integrated with the Unity Editor was installed on a desktop computer and configured to develop the Android AR app for the visualization of internal organs. Three-dimensional segmented human organs were extracted from a computerized tomography file using Seg3D software, and overlaid on a target body surface through the developed app with an artificial marker. Results: To aid beginners in using the AR technology for medical applications, a 3D model of the thyroid and surrounding structures was created from a thyroid cancer patient's DICOM file, and was visualized on the neck of a medical training mannequin through the developed AR app. The individual organs, including the thyroid, trachea, carotid artery, jugular vein, and esophagus were localized by the surgeon's Android smartphone. Conclusions: Vuforia software can help even researchers, students, or surgeons who do not possess computer vision expertise to easily develop an AR app in a user-friendly manner and use it to visualize and localize critical internal organs without incision. It could allow AR technology to be extensively utilized for various medical applications.

• Journal of Industrial Convergence
• /
• v.17 no.2
• /
• pp.45-52
• /
• 2019

A systematic review was conducted to identify components and convergent effects of simulation program using schizophrenia scenario in nursing education. Using 4 different databases, 226 articles were identified and 11 studies met the inclusion criteria. There were 5 qualitative studies, 5 quantitative studies and 1 study used mixed method design. The simulation incorporated various methods including standardized patients, role playing, simulator and virtual reality that majority studies(63.6%) used standardized patients. For the evaluation, studies examined diverse variables including knowledge, learning self competency, learning satisfaction and self directed learning. Considering complexity and difficulty of nursing for schizophrenia, future studies with well designed simulation program are required to prove its effectiveness.

• KEPCO Journal on Electric Power and Energy
• /
• v.4 no.2
• /
• pp.101-105
• /
• 2018

In this paper, the kernel regression model is applied for the case study of gas turbine abnormal state analysis. In addition to vibration analysis at the remote site, the kernel regression model technique can is useful for analyzing abnormal state of rotor vibration signals of gas turbine in power plant. In monitoring based on data-driven techniques correlated measurements, the fault free training data of shaft vibration obtained during normal operations of gas turbine are used to develop a empirical model based on auto-associative kernel regression. This data-driven model can be used to predict virtual measurements, which are compared with real-time data, generating residuals. Any faults in the system may cause statistically abnormal changes in these residuals and could be detected. As the result, the kernel regression model provides information that can distinguish anomalies such as sensor failure in a shaft vibration signal.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.75-80
• /
• 2021

Positioning technology is performing important functions in augmented reality, smart factory, and autonomous driving. Among the positioning techniques, the positioning method using beacons has been considered a challenging task due to the deviation of the RSSI value. In this study, the position of a moving object is predicted by training a neural network that takes the RSSI value of the receiver as an input and the distance as the target value. To do this, the measured distance versus RSSI was collected. A neural network was introduced to create synthetic data from the collected actual data. Based on this neural network, the RSSI value versus distance was predicted. The real value of RSSI was obtained as a neural network for generating synthetic data, and based on this value, the coordinates of the object were estimated by learning a neural network that tracks the location of a terminal in a virtual environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.4
• /
• pp.1502-1520
• /
• 2021

This paper attempts to investigate Korean youth Not in Education, Employment and Training (NEET) and how daily activities and community participation may influence their positive emotions and job search desire. First, we conducted a focus group interview with 16 NEETs who participated in the Kakao NEET Company project. The project allowed participants to experience employment by founding a virtual company in which each participant selected a daily activity to perform as part of the company's operations. Second, the interview responses were categorized and assigned emotional values using the card sorting technique and multi-dimensional analysis (MDS). A total of 11 emotional values were derived through this process. Finally, a social network analysis was conducted in order to measure the density of relations among the emotional values. Results suggest that immersion, confidence, belongingness were the three highest values evaluated by participants. Furthermore, network diagrams imply that the stronger participants perceived social support and belongingness with others, the stronger their responsibility grew, further leading them to establish steady goals. In particular, the high eigenvector score for "desire for job" suggests that emotional values are sequentially connected to the immersion-social support-responsibility-goal-job desire. This sequence suggests that digital services that are developed with the aim to enhance social values such as the Kakao NEET Project may engender motivation and confidence in youth NEETs. The overall results suggest that a systematic approach to policymaking should be considered in order to provide fundamental solutions and expand opportunities for social participation and emotional comfort, as social isolation due to low self-esteem has been reported as one of the reasons for NEETs' failure in the labor market.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.25 no.6
• /
• pp.617-627
• /
• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.2
• /
• pp.626-643
• /
• 2023

As mobile forensics has emerged as an essential technique, the demand for technology development, education and training is increasing, wherein images are used. Academic societies in South Korea and national institutions in the US and the UK are leading the Mobile Forensic Image development. However, compared with disks, images developed in a mobile environment are few cases and have less active research, causing a waste of time, money, and manpower. Mobile Forensic Images are also difficult to trust owing to insufficient verification processes. Additionally, in South Korea, there are legal issues involving the Telecommunications Business Act and the Act on the Protection and Use of Location Information. Therefore, in this study, we requested a review of a standard model for the development of Mobile Forensic Image from experts and designed an 11-step development model. The steps of the model are as follows: a. setting of design directions, b. scenario design, c. selection of analysis techniques, d. review of legal issues, e. creation of virtual information, f. configuring system settings, g. performing imaging as per scenarios, h. Developing a checklist, i. internal verification, j. external verification, and k. confirmation of validity. Finally, we identified the differences between the mobile and disk environments and discussed the institutional efforts of South Korea. This study will also provide a guideline for the development of professional quality verification and proficiency tests as well as technology and talent-nurturing tools. We propose a method that can be used as a guide to secure pan-national trust in forensic examiners and tools. We expect this study to strengthen the mobile forensics capabilities of forensic examiners and researchers. This research will be used for the verification and evaluation of individuals and institutions, contributing to national security, eventually.