• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.671-674
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• 2012

Recently, depending on the development of smart devices, a variable services have been offered to meet user's convenience. Due to these advance, the needs of users are extremely being diversified and more specific. In that situation, the needs for the N-Screen system has been varied and gradually evolved. An existing N-Screen system that use the way of video streaming upload its multimedia contents to their own cloud server so that might take a long play-reaction time and the number of user is limited by the server's performance. Because of the web based protocol adopted by existing N-Screen system, there are many different problems like high delay, overhead and something caused by simplex data communications. Therefore, to solve the problems above, this study proposes an application based on HTML5. This application supports Video tag and Progressive download via HTML5 so that improves the play-reaction time for multimedia contents. This system can also get rid of the chronic problems such as an access limitation for lots of users as per video streaming encoding. Also, through web sockets, this study proposes a system that has lower delay than the existing system and communicates in full duplex to be able to link dynamically.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.1-11
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• 2016

Currently Korean government is rushing the new electronic government system introduced as 'platform e-government' with big data and cloud computing technologies and systems, ultimately intending to provide the public institution services customized from the integrated counter or window for the heterogeneous resident services. In this regard, this study suggested how to design the new metadata information system in which mutual integration of information systems can take place, where heterogeneous services can be shared efficiently at the application and data unit, as a separate application that can provide a single one- stop service for residents' petition at the integrated level in the back-office based on the public data in possession of each of government ministries and related organizations. If this proposed system is implemented, the achievement of customized public service can be advanced one step forward in processing the petitions of the residents by organically connected link between 'Demand Chain' and 'Supply Chain' in the integrated window. In other words, it could be made possible through the unification of both the 'Supply Chain' performed in the office space of the officials at the back-office level and the 'Demand Chain' performed in the living space of the residents at the front-office level.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.15-24
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• 2015

The trade balance for the information and communications technology (ICT) industries in 2014 have reached 863 hundred million dollars as the main export products such as smart phone and semi-conductor increase, since the ICT industries have played an important role in economic growth in Korea. Until now, the consistent supporting of government and investment of company have been doing with the growth of ICT industries, as a result, Korea marked as the first in the UN electronic government preparing index, and rank 12 in the network preparing index through the policy of national information and basic plan of inter-industry convergence. However, as the unstable international economic circumstances, ICT industries is faced with the stagnation, and then preemptive development of products and services for ICT convergence industries is needed to continually get definite ICT Korea image. In this paper, the ICT convergence industry is analyzed and forecasted. In specific, the international and domestic market for cloud, 3D convergence, and internet of things is diagnosed. The market for ICT convergence industries is predicted to be 3.6 trillion dollar in the world, and 110 trillion won in domestic. From the analytical results for technology and services development, the preemptive supporting of the technology development and policy for the internet of things and 3D convergence industries is required. In addition to, through the future forecasting by socio-tech matrix method, the policy supporting for the ICT convergence area of healthcare, fintech, artificial intelligence, body platform, and human security is needed.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.62-77
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• 2019

Open Data Cube(ODC) has been emerging and developing as the open source platform in the Committee on Earth Observation Satellites(CEOS) for the Global Earth Observation System of Systems(GEOSS) deployed by the Group on Earth Observations (GEO), ODC can be applied to the deployment of scalable and large amounts of free and open satellite images in a cloud computing environment, and ODC-based country or regional application services have been provided for public users on the high performance. This study first summarizes the status of ODC, and then presents concepts and some considering points for linking this platform with Korea Multi-Purpose Satellite (KOMPSAT) images. For the reference, the main contents of ODC with the Google Earth Engine(GEE) were compared. Application procedures of KOMPSAT satellite image to implement ODC service were explained, and an intermediate process related to data ingestion using actual data was demonstrated. As well, it suggested some practical schemes to utilize KOMPSAT satellite images for the ODC application service from the perspective of open data licensing. Policy and technical products for KOMPSAT images to ODC are expected to provide important references for GEOSS in GEO to apply new satellite images of other countries and organizations in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.29-43
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• 2022

With the advent of the Internet and the development of mobile digital devices such as smartphones and tablet PCs, the communication service paradigm began to shift from existing voice services to data services. Recently, as social network services (SNS) are activated and 4th industrial revolution technologies centered on ICT (Information and Communication Technologies) such as Big Data, Blockchain, Cloud, and 5G/6G are rapidly developed, the amount of shared data type and the amount of data are increasing rapidly. As the transition to a digital society begins actively, the importance of using data information, as well as the economic and social values of personal information are becoming increasingly important. As a result, they are actively discussing policies to revitalize the data information industry around the world and ways to efficiently obtain, analyze, and utilize increasingly diverse and vast data, as well as to protect/guarantee the rights of information subjects (providers) in various fields such as society, culture, economy, and politics.. In this paper, in order to improve the self-determination right of personal information on data produced by information subjects, and further expand the use of safe data and the data economy, a differentiated data trusts system was considered and suggested. In addition, the components and data trusts procedures necessary to efficiently operate the data trusts system in Korea were considered, and the non-profit data trusts system and the for-profit data trusts system were considered as a way to flexibly operate the data trusts system. Furthermore, the legal items necessary for the implementation of the data trusts system were investigated and considered. In this paper, in order to propose a domestic data trusts system, cases related to existing data trusts systems such as the United States, Japan, and Korea were reviewed and analyzed. In addition, in order to prepare legislation necessary for the data trusts system, data-related laws in major countries and domestic legal and policy trends were reviewed to study the rights that conflict or overlap with existing laws, and differences were investigated and considered. The Data trusts system proposed in this paper is a reasonable system that is expected to recognize the asset value of data in the capitalist market economy system, to provide legitimate compensation for data produced by data subjects, and further to contribute greatly to the use of safe data and creation of a new service market.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.715-720
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• 2023

The military is driving innovative changes such as AI, cloud computing, and drone operation through the Fourth Industrial Revolution. It is expected that such changes will lead to a rapid increase in the demand for information exchange requirements, reaching all lower-ranking soldiers, as networking based on IoT occurs. The flow of such information must ensure efficient information distribution through various infrastructures such as ground networks, stationary satellites, and low-earth orbit small communication satellites, and the demand for information exchange that is distributed through them must be appropriately dispersed. In this study, we redefined the DSCP, which is closely related to QoS (Quality of Service) in information dissemination, into 11 categories and performed research to map each cluster group identified by cluster analysis to the defense "information exchange requirement list" on a one-to-one basis. The purpose of the research is to ensure efficient information dissemination within a multi-layer integrated network (ground network, stationary satellite network, low-earth orbit small communication satellite network) with limited bandwidth by re-establishing QoS policies that prioritize important information exchange requirements so that they are routed in priority. In this paper, we evaluated how well the information exchange requirement lists classified by cluster analysis were assigned to DSCP through M&S, and confirmed that reclassifying DSCP can lead to more efficient information distribution in a network environment with limited bandwidth.

• Information Systems Review
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• v.25 no.4
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• pp.183-204
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• 2023

Due to the COVID-19 pandemic, lots of occasions need to be held in online environment. This is the reason why "Metaverse" gets lots of attention in 2021. A number of companies made announcements on Metaverse, and this situation also boomed stock market. This paper investigates the relationship between Metaverse initiatives and business value of the firm (i.e., stock prices). We examine this relationship by using event study method with Lexis-Nexis News data from 2019 to 2021. The results indicate that Metaverse initiatives significantly impact positive influence on firm's value. In the technological perspective, technical factors affect more positive market returns, including Metaverse enablers (e.g., NFT, VR devices, digital twin) and common infrastructure (e.g., semiconductor, AI, cloud), and especially virtual environment was emphasized. Additionally, in the strategical perspective, radical innovation (e.g., pivoting, acquisition) impact more positive market return rather than incremental innovation (e.g., partnership, investment). Also, firms from non-service industries can achieve benefits from Metaverse initiatives rather than service industry in some degree.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.147-153
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• 2023

As it spreads to all industries of artificial intelligence technology, AIaaS equipped with artificial intelligence services is emerging. In particular, non-IT companies are suffering from the absence of software experts, difficulties in training big data models, and difficulties in collecting and analyzing various types of data. AIaaS makes it easier and more economical for users to build a system by providing various IT resources necessary for artificial intelligence software development as well as functions necessary for artificial intelligence software in the form of a service. Therefore, the supply and demand for such cloud-based AIaaS services will increase rapidly. However, the quality of services provided by AIaaS becomes an important factor in what is required as the supply and demand for AIaaS increases. However, research on a comprehensive and practical quality evaluation metric to measure this is currently insufficient. Therefore, in this paper, we develop and propose a usability, replacement, scalability, and publicity metric, which are the four metrics necessary for measuring reusability, based on implementation, convenience, efficiency, and accessibility, which are characteristics of AIaaS, for reusability evaluation among the service quality measurement factors of AIaaS. The proposed metrics can be used as a tool to predict how much services provided by AIaaS can be reused for potential users in the future.