• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.53-61
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• 2022

Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Journal of the Korean Institute of Gas
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• v.27 no.1
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• pp.57-62
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• 2023

The Gas Regulator EVENT is a signal sent by the Remote Terminal Unit(RTU) installed in each local gas regulator (hereinafter referred to as "regulator"), and is an abnormal alarm that can be intuitively checked in our client server. This is an important data that enables immediate dispatch order and initial action in the situation room when a regolator abnormality occurs, and can analyze the cause of the regulator abnormality. Looking at the trend of EVENT data for regulator over the past three years, there is a clear trend of increasing unchecked EVENT data. The increase in non-checking event (actual abnormality or noise event) may mean that firstly, mechanical or pressure abnormality occurs in the actual regulator, and secondly, there is no abnormality in the actual regulator, but communication error occurred in the RTU, reset. EVENT Data may be formed as if an abnormality occurred in the static voltage due to an error, sensor error, power failure (instantaneous power failure), etc. Among them, this study analyzed the recently generated unchecked EVENT data to identify critical noise events among RTU errors, which are noise events, and reviewed ways to increase the reliability of Regulator EVENTs by reducing them.

• Knowledge Management Research
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• v.23 no.4
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• pp.251-273
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• 2022

Metaverse is one of the most frequently used words recently, with digitalization accelerated by the COVID-19 pandemic that started in 2019 and the development of information and communication technology. It is expected to bring a new revolution in our life as a whole in user experience. In particular, as telecommuting was adopted in the business area, interest in virtual office services such as digital video conferencing and remote offices, which are similar to the metaverse, has also increased. In this study, a study on the intention to use the metaverse service used in the work environment was applied to the Unified Theory of Acceptance and Use of Technology 2(UTAUT2). External variables for metaverse characteristics, such as self-presentation, telepresence, and technostress, were analyzed and discussed. In this study, PC-based Gather.town and VR-based Facebook Horizon, currently the most well-known and considered usable in work environments, were introduced to potential users and conducted a survey. This study has academic implications in that the research has examined the factors that affect the technology acceptance intention of users who want to apply the metaverse as a work environment based on the UTAUT2 model, unlike previous studies that have been mainly researched on the general metaverse. In practice, it may be helpful to suggest factors that should be considered when firms adopt the metaverse for business purposes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1577-1585
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• 2022

As the interest in the 4th industrial revolution and metaverse increases, metaverse with multi edge structure is proposed and noted. Metaverse is a structure that can create digital doctor-like system through a large amount of image processing and data transmission in a multi edge system. Since metaverse application requires calculating performance, which can reconstruct 3-D space, edge hardware's insufficient calculating performance has been a problem. To provide streamable AI software in runtime, image processing, and data transmission, which is edge's loads, needs to be lightweight. Also lightweight at the edge leads to power consumption reduction of the entire metaverse application system. In this paper, we propose collaborative edge-cloud image processing with remote image processing method and Region of Interest (ROI) to overcome edge's power performance and build streamable and runtime executable AI software. The proposed structure was implemented using a PC and an embedded board, and the reduction of time, power, and network communications were verified.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.94-99
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• 2024

Recently, wind power has been gaining attention as a highly efficient renewable energy source, leading to various technological developments worldwide. Typically, wind power is operated in the form of large wind farms with many wind turbines installed in areas rich in wind resources. However, in developing countries or regions isolated from the power grid, off-grid small wind power systems are emerging as an efficient solution. To efficiently operate and expand off-grid small-scale power systems, the development of real-time monitoring systems is required. For the efficient operation of small wind power systems, it is essential to develop real-time monitoring systems that can actively respond to excessive wind speeds and various environmental factors, as well as ensure the stable supply of produced power to small areas or facilities through an Energy Storage System (ESS). The implemented system monitors turbine RPM, power generation, brake operation, and more to create an optimal operating environment. The developed small wind power system can be utilized in remote road lighting, marine leisure facilities, mobile communication base stations, and other applications, contributing to the development of the RE100 industry ecosystem.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.101-116
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• 2018

Sustainability science is an emerging transdisciplinary research which necessitates not only the communication and collaboration of scientists, practitioners and stakeholders from different disciplines and interests, but also the paradigm shift from deterministic and reductionist approaches to the old basic. Ecological-societal systems (ESS) are co-evolving complex systems having many interacting parts (or agents) whose random interactions at local scale give rise to spontaneous emerging order at global scale (i.e., self-organization). Here, the flows of energy, matter and information between the systems and their surroundings play a key role. We introduce a conceptual framework for such continually morphing dynamical systems, i.e. self-organizing hierarchical open systems (SOHOs). To understand the structure and functionality of SOHOs, we revisit the two fundamental laws of physics. Re-interpretation of these principles helps understand the destiny and better path toward sustainability, and how to reconcile ecosystem integrity with societal vision and value. We then integrate the so-called visioneering (V) framework with that of SOHOs as feedback/feedforward loops so that 'a nudged self-organization' may guide systems' agents to work together toward sustainable ESS. Finally, example is given with newly endorsed Sustainable Development Goals (SDG) Lab (i.e., 'Rural systems visioneering') by Future Earth, which is now underway in rural villages in Tanzania.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.278-283
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• 2000

As information communication technology developed we could check our blood pressure, pulsation electrocardiogram, SpO2 and blood test easily at home. To check our health at ordinary times is able though interlocking the house medical instrument with the wireless public data network This service will help the inconvenience to visit the hospital everytime and will save the individual's time and cost. In each house an organism data which is detected from the human body will be transmitted to the distance hospital and will be essentially applied through wireless public data network The medical information transmit system is utilized by wireless close range network It would transmit the obtained organism signal wirelessly from the personal device to the main center system in the hospital. Remote telemetry system is embodied by utilizing wireless media access protocol. The protocol is embodied by grafting CSMA/CA(Carrier Sense Multiple Access with Collision Avoidance) protocol falling mode which is standards from IEEE 802.11. Among the house care telemetry system which could measure blood pressure, pulsation, electrocardiogram, SpO2 the study embodies the ECC(electrocardiograph) measure part. It within the ECC function into the movable device and add 900㎒ band wireless public data interface. Then the aged, the patients even anyone in the house could obtain ECG and keep, record the data. It would be essential to control those who had a health-examination heart diseases or more complicated heart diseases and to observe the latent heart disease patient continuously. To embody the medical information transmit system which is based on wireless network. It would transmit the ECG data among the organism signal data which would be utilized by wireless network modem and NCL(Native Control Language) protocol to contact through wireless network Through the SCR(Standard Context Routing) protocol in the network it will be connected to the wired host computer. The computer will check the recorded individual information and the obtained ECC data then send the correspond examination to the movable device. The study suggests the medical transmit system model utilized by the wireless public data network.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.1
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• pp.31-46
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• 2012

The most critical technology to implement ubiquitous health care is Ubiquitous Sensor Network (USN) technology which makes use of various sensor technologies, processor integration technology, and wireless network technology-Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN)-to easily gather and monitor actual physical environment information from a remote site. With the feature, the USN technology can make the information technology of the existing virtual space expanded to actual environments. However, although the RFID and the WSN have technical similarities and mutual effects, they have been recognized to be studied separately, and sufficient studies have not been conducted on the technical integration of the RFID and the WSN. Therefore, EPCglobal which realized the issue proposed the EPC Sensor Network to efficiently integrate and interoperate the RFID and WSN technologies based on the international standard EPCglobal network. The proposed EPC Sensor Network technology uses the Complex Event Processing method in the middleware to integrate data occurring through the RFID and the WSN in a single environment and to interoperate the events based on the EPCglobal network. However, as the EPC Sensor Network technology continuously performs its operation even in the case that the minimum conditions are not to be met to find complex events in the middleware, its operation cost rises. Moreover, since the technology is based on the EPCglobal network, it can neither perform its operation only for the sake of sensor data, nor connect or interoperate with each information system in which the most important information in the ubiquitous computing environment is saved. Therefore, to address the problems of the existing system, we proposed the design and implementation of USN integration management system. For this, we first proposed an integration system that manages RFID and WSN data based on Session Initiation Protocol (SIP). Secondly, we defined the minimum conditions of the complex events to detect unnecessary complex events in the middleware, and proposed an algorithm that can extract complex events only when the minimum conditions are to be met. To evaluate the performance of the proposed methods we implemented SIP-based integration management system.