• Journal of the Korean Society for information Management
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• v.31 no.2
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• pp.7-40
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• 2014

This study proposes to identify digital library services applying cutting-edge technologies, and attempt to investigate the applicability of these technologies and services to domestic libraries. To this end, we reviewed main research which discusses next generation digital libraries, and examined thoroughly main technologies which can be applied to future libraries. As a result, the core technologies, concepts, and tools of the next generation of digital library are: cloud services, space for infinite creating (makerspace), big data, augmented reality, context-aware technologies, Google-glass, a revolutionary display technology, open linked-content-offering method, and so on. Specific cases of libraries already utilizing these technologies are also discussed.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.42-50
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• 2018

The majority of existing falling recognition techniques provide service by recognizing only that the falling occurred. However, it is important to recognize not only the occurrence of falling but also the situation before and after the falling, as well as the location of the falling. In this paper, we design and propose the falling notification service system to recognize and provide service. This system uses the acceleration sensor of the smartphone to recognize the occurrence of a falling and the situation before and after the falling. In order to check the location of falling, GPS sensor data is used in the Google Map API to map to the map. Also, a crosswalk map converted into grid-based coordinates based on the longitude and latitude of the crosswalk is stored, and the locations before and after falling are mapped. In order to reduce the connection speed and server overload for real-time data processing, fog computing and cloud computing are designed to be distributed processing.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.40-42
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• 2011

Smart hand-held devices like iPhone, iPad, Andriod and other mobile-OS machines are becoming a well known part of our daily lives. Utilization of these devices has gone beyond the expectations of their inventors. Evolution of Apple's iOS from a mobile phone Operating System to a wholesome platform for Portable Gaming is an adequate proof. Using these smart devices people are downloading applications from numerous online App Stores. Utilizing remote storage facilities and confining themselves to computing power far below than an entry level laptop, netbooks have emerged. Google's idea of Chrome OS coupled with Google's AppEngine is an eye-opener for researchers and developers. Keeping all these industry-proven innovations in mind we are proposing a Context-Driven Cloud-Oriented Application Architecture for smart devices. This architecture enables our smart devices to behave smarter by utilizing very less of local resources.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.01a
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• pp.155-158
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• 2015

클라우드 컴퓨팅 기술의 발전과 맞물려서 이를 위한 많은 플랫폼들이 제안되고 있다. Amazon이나 Google 등의 세계적인 기업들을 이미 자신들 만의 플랫폼을 구축하여 안정적으로 서비스를 제공하고 있으며 오픈소스 커뮤니티들이 주도 하는 오픈 플랫폼들도 속속 등장하여 발전을 거듭하고 있다. 본 논문에서는 가장 대표적이고 널리 사용되는 오픈소스 기반의 클라우드 컴퓨팅 플랫폼들을 분석하고 그 기능들을 서로 비교해서 사용자가 자신의 요구사항에 가장 적합한 플랫폼을 선택할 수 있게 한다.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.45-49
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• 2022

The fourth industrial revolution, internet of things, and the expansion of online web services have increased an exponential growth and deployment in the number of cloud data centers (CDC). The cloud is emerging as new paradigm for delivering the Internet-based computing services. Due to the dynamic and non-linear workload and availability of the resources is a critical problem for efficient workload and resource management. In this paper, we propose the particle swarm optimization (PSO) based gated recurrent unit (GRU) neural network for efficient prediction the future value of the CPU and memory usage in the cloud data centers. We investigate the hyper-parameters of the GRU for better model to effectively predict the cloud resources. We use the Google Cluster traces to evaluate the aforementioned PSO-GRU prediction. The experimental shows the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.757-760
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• 2012

Cloud storage system that cloud computing providers provides large amounts of data storage and processing of cloud computing is a key component. Large vendors (such as Facebook, YouTube, Google) in the mass sending of data through the network quickly and easily share photos, videos, documents, etc. from heterogeneous devices, such as tablets, smartphones, and the data that is stored in the cloud storage using was approached. At time, growth and development of the globally data, the cloud storage business model emerging is getting. Analysis new network storage cloud storage services concepts and technologies, including data manipulation, storage virtualization, data replication and duplication, security, cloud computing core.

• Journal of Information Technology and Architecture
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• v.10 no.4
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• pp.509-516
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• 2013

Cloud services are recognized the essential IT infrastructure in the optimal smart society which is changing rapidly as a low-cost and high-efficiency. This service of starting from prominent overseas companies such as Google, Amazon, had influenced on the introduction of the service for the various policies of foreign governments, including the United States and the United Kingdom. Such countries adopting to the cloud computing and make transform to the cloud service of existing public service for the effective management of information resources. In this study, we have proposed the main determining factors of cloud adoption, the model of cloud governance for the adoption of public cloud service.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.174-183
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• 2021

This study aims to suggest a method to provide a real-time noise map based on cloud using Amazon AWS. Acquiring environmental noise information, an Android app was developed to collect data on noise level, location, and measurement time of campus in Inha Technical College as a study area. Noise measurement information is transmitted to the AWS Cloud and managed, and the noise information collected through Amazon Quick Site is displayed in charts and maps. Finally, a web-based noise contour map and the results mapped to buildings were visualized with a Google map for users to search for the current environmental noise distribution. The real-time noise map presented as a result of this study is expected to be helpful for noise status and reduction policies.

• Korean Journal of Remote Sensing
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• v.40 no.3
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• pp.285-293
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• 2024

This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT),the research utilizes GEE's cloud computing capabilities to handle and analyze large datasets. The study employs Otsu's method for image binarization to distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January 2016 to January 2024, primarily due to calving events,while DIT showed a slight increase overall,with notable reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy,underscoring the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.10-13
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• 2015

Google App Engine(GAE)은 플랫폼 서비스 형태(Platform as a Service, PaaS)의 클라우드 인프라이며 GAE를 기반으로 웹어플리케이션을 제작할 수 있도록 다양한 개발 도구를 제공해 준다. 본 논문에서는 Python 및 Go를 이용하여 GAE 상에서 구현한 클라우드 기반의 web application들의 성능을 비교하고자 한다. 각 web application의 주요 기능은 회원가입, 로그인, 채팅 등으로 구성되어 있고 특히, 회원목록이나 채팅 데이터를 처리하기 위하여 GAE에서 제공하는 Google Datastore를 사용하였다. 성능비교를 위하여 Python2.5, Python 2.7 및 Go를 사용하여 통일한 기능의 web application을 구현하였으며 각각의 메뉴에 대하여 서버 로직의 실행과 장고 (Django) 스타일의 HTML 템플릿을 렌더링하는데 걸리는 시간을 구하고 이를 비교 분석하였다.