• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.79-105
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• 2023

Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.90-98
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• 2017

Since 2010, SNS was holding the explosive spread of smartphones has created a place of public advertising platform, and it entered the Internet of Things (IoT) is born gradually countdown of the era came to us already. In utilizing a variety of location-based services IoT services (beacon, O2O) The focus of this paper to analyze the differences in satisfaction with the oil layer by experienced users of what is being used. We consider the type and overall utilization of the concepts typical IoT service in the current service is made to expand the contents of the paper. Hypothesis was reconstructed ease, attractiveness, a survey reliability, value four kinds of models, called Honeycomb UX, User Experience Honeycomp Peter Mobil. Company that provides the service IoT in this study are expected to be used as basic data to help provide a more accurate personalized service according to the user's satisfaction difference.

• Informatization Policy
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• v.26 no.1
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• pp.3-24
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• 2019

This study examined the trends and issues of social media campaign studies from three aspects-campaign strategy, institutional environment regulating the social media, and political effect. Then, this study performed an empirical analysis on the case of the 20th general election in order to discuss the political effect, which has been analyzed the least. Specifically, this study empirically examined the trends of candidates' participation in the twitter campaign, the partial mobilization and voter response, and the platform effect on the election results. The study examined all of the candidates' twitter accounts and traffic and found the following results.-first, the number of participants in the twitter campaign increased significantly compared to the 19th general election, and the campaign was dominated by only two political parties that had more power to mobilize resources; second, it was clearly identified that twitter is a partisan media. where specifically, those in the mainstream of the Democratic Party mobilized much more supporters; and lastly, the twitter campaign has a positive impact on the increase in the rate of votes and chances of winning the election. Particularly, the number of followers and the duration of activities were found statistically meaningful, proving that promotion of networking and social capital is more important in election campaigns.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.1
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• pp.9-18
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• 2018

Enhancing performance of big data analytics in distributed environment has been issued because most of the big data related applications such as machine learning techniques and streaming services generally utilize distributed computing frameworks. Thus, optimizing performance of those applications at Spark has been actively researched. Since optimizing performance of the applications at distributed environment is challenging because it not only needs optimizing the applications themselves but also requires tuning of the distributed system configuration parameters. Although prior researches made a huge effort to improve execution performance, most of them only focused on one of three performance optimization aspect: application design, system tuning, hardware utilization. Thus, they couldn't handle an orchestration of those aspects. In this paper, we deeply analyze and model the application processing procedure of the Spark. Through the analyzed results, we propose performance optimization schemes for each step of the procedure: inner stage and outer stage. We also propose appropriate partitioning mechanism by analyzing relationship between partitioning parallelism and performance of the applications. We applied those three performance optimization schemes to WordCount, Pagerank, and Kmeans which are basic big data analytics and found nearly 50% performance improvement when all of those schemes are applied.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.313-321
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• 2014

In current society, the digital era that makes enormous amount of data, and the diversified city, the smart space, which has characteristics of creating, collecting and representing data, is appeared. After 2012, in the social media environment called hyper-connected society with wide-spread smart phone, people started to get interested in public data and big data by generalized mobile device and SNS. At first, development of forming platform of data was focused, but now, many different idea from diverse area have been suggested about data analysis and usage to visualize the space intellectualization service. To focus on the visualization process to increase the usage of this public data for ordinary people more than specialized people, this research grasps the present condition of open data and public data service from the current public data portal and considers the applicability of them. As the result of research, the analysis and application of data to ordinary people decrease the use of paper documents, and this research will help to develop the application which is fast and accurate about individual behavior and demand to utilize public data service in intellectual space.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.119-130
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• 2015

In recent years, the attention on the applications of the national or international standards to water-related information technology in practice has more increased. In particular, as the demand on spatial information technology including content development, receiving, disposal and distribution has increased, the importance of standardization has been also emphasized. However, compared with attention and demand on standardization in spatial information technology, studies on development and application of standardization are still at the initial stage. Accordingly, this study attempted to investigate the trends of international standards developed and established by International Organization for Standardization(ISO) and Open Geospatial Consortium(OGC), and to derive the adaptable integrated management standard technology for water hazard information platform. For this, we investigated big data, NoSQL, and cloud technology for the observed data provision. Furthermore, OGC WxS standard technologies for spatial information web service and ISO standards for spatial information format were investigated. Based on these investigations, we examined the strategies and plans to apply and establish the standardization for information provision.

• Journal of Convergence for Information Technology
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• v.9 no.12
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• pp.1-7
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• 2019

As the cloud environment has become more prevalent among large companies, small and medium-sized companies are also trying to utilize various technologies (IoT, blockchain, etc.) that use cloud services as a way to coexist with large companies. In this paper, a blockchain-based IoT information collection model is proposed to efficiently handle large volumes of IoT data produced by small businesses in order to improve information efficiency of SMEs. The proposed model allowe d small businesses to improve their production efficiency by independently creating groups of the same information so that data that could be generated at the endpoints of small businesses can be block-chained and forwarded to the data center for analysis. In addition, the proposed model's performance assessment was assumed to handle the production throughput of data processed in IoT for small and medium businesses, not large enterprises, so the link between large volumes of data processed in the proposed model could be maintained evenly. One of the biggest features of the proposed model is the ability to expand processes to efficiently control the information of prod ucts produced, as well as the productivity of small and medium enterprises.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.565-572
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• 2020

This study developed a software platform using machine learning of artificial intelligence to optimize the distillation column system. The distillation column is representative and core process in the petrochemical industry. Process stabilization is difficult due to various operating conditions and continuous process characteristics, and differences in process efficiency occur depending on operator skill. The process control based on the theoretical simulation was used to overcome this problem, but it has a limitation which it can't apply to complex processes and real-time systems. This study aims to develop an empirical simulation model based on machine learning and to suggest an optimal process operation method. The development of empirical simulations involves collecting big data from the actual process, feature extraction through data mining, and representative algorithm for the chemical process. Finally, the platform for the distillation column was developed with verification through a developed model and field tests. Through the developed platform, it is possible to predict the operating parameters and provided optimal operating conditions to achieve efficient process control. This study is the basic study applying the artificial intelligence machine learning technique for the chemical process. After application on a wide variety of processes and it can be utilized to the cornerstone of the smart factory of the industry 4.0.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.2
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• pp.59-75
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• 2019

This study was carried out to explore the 4th Industrial Revolution technology from the perspective of the landscape industry to provide the basic data necessary to increase the virtuous circle value. The 4th Industrial Revolution, the characteristics of the landscape industry and urban regeneration were considered and the methodology was established and studied including the technical classification system suitable for systematic research, which was selected as a framework. First, the 4th Industrial Revolution technology based on digital data was selected, which could be utilized to increase the value of the virtuous circle for the landscape industry. From 'Element Technology Level', and 'Core Technology' such as the Internet of Things, Cloud Computing, Big Data, Artificial Intelligence, Robot, 'Peripheral Technology', Virtual or Augmented Reality, Drones, 3D 4D Printing, and 3D Scanning were highlighted as the 4th Industrial Revolution technology. It has been shown that it is possible to increase the value of the virtuous circle when applied at the 'Trend Level', in particular to the landscape industry. The 'System Level' was analyzed as a general-purpose technology, and based on the platform, the level of element technology(computers, and smart devices) was systematically interconnected, and illuminated with the 4th Industrial Revolution technology based on digital data. The application of the 'Trend Level' specific to the landscape industry has been shown to be an effective technology for increasing the virtuous circle values. It is possible to realize all synergistic effects and implementation of the proposed method at the trend level applying the element technology level. Smart gardens, smart parks, etc. have been analyzed to the level they should pursue. It was judged that Smart City, Smart Home, Smart Farm, and Precision Agriculture, Smart Tourism, and Smart Health Care could be highly linked through the collaboration among technologies in adjacent areas at the Trend Level. Additionally, various utilization measures of related technology applied at the Trend Level were highlighted in the process of urban regeneration, public service space creation, maintenance, and public service. In other words, with the realization of ubiquitous computing, Hyper-Connectivity, Hyper-Reality, Hyper-Intelligence, and Hyper-Convergence were proposed, reflecting the basic characteristics of digital technology in the landscape industry can be achieved. It was analyzed that the landscaping industry was effectively accommodating and coordinating with the needs of new characters, education and consulting, as well as existing tasks, even when participating in urban regeneration projects. In particular, it has been shown that the overall landscapig area is effective in increasing the virtuous circle value when it systems the related technology at the trend level by linking maintenance with strategic bridgehead. This is because the industrial structure is effective in distributing data and information produced from various channels. Subsequent research, such as demonstrating the fusion of the 4th Industrial Revolution technology based on the use of digital data in creation, maintenance, and service of actual landscape space is necessary.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.