• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.7-13
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• 2021

Recently, due to the many features and advantages of cloud computing, cloud service is being introduced to countless industries around the world at an unbelievably rapid pace. With the rapid increase in the introduction of multi-cloud based services, security vulnerabilities are increasing, and the risk of data leakage from cloud computing services are also expected to increase. Therefore, this study will propose an AWS Well-Architected based security architecture configuration method such as AWS standard security architecture, AWS shared security architecture model that can be applied for personal information security including cost effective of cloud services for better security in AWS cloud service. The AWS security architecture proposed in this study are expected to help many businesses and institutions that are hoping to establish a safe and reliable AWS cloud system.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.6
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• pp.177-186
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• 2020

Recent advances in deep learning technology have improved image recognition performance in the field of computer vision, and serverless computing is emerging as the next generation cloud computing technology for event-based cloud application development and services. Attempts to use deep learning and serverless computing technology to increase the number of real-world image recognition services are increasing. Therefore, this paper describes how to develop an efficient deep learning based image recognition service system using serverless computing technology. The proposed system suggests a method that can serve large neural network model to users at low cost by using AWS Lambda Server based on serverless computing. We also show that we can effectively build a serverless computing system that uses a large neural network model by addressing the shortcomings of AWS Lambda Server, cold start time and capacity limitation. Through experiments, we confirmed that the proposed system, using AWS Lambda Serverless Computing technology, is efficient for servicing large neural network models by solving processing time and capacity limitations as well as cost reduction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.7-12
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• 2022

This paper introduces the implementation of the AWS IoT service and MQTT based smart home system. The smart home system implemented in this study can monitor temperature and humidity, and can manually adjust the air conditioner heating, and can check the visitors with the camera and remotely control the door lock. The implemented smart home system controls door locks, heating and air conditioners using Arduino, and manages the collected data and control information using the AWS IoT service. In this study, the Android app has been developed to allow users to control IoT devices remotely, and the MQTT protocol was used for data communication and control between the app and the AWS IoT server and Arduino. The implemented smart home system has been implemented based on AWS IoT service, which has scalability to add sensors and devices.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Korean Journal of Remote Sensing
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• v.18 no.6
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• pp.319-326
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• 2002

Rainfall estimation was conducted based on TRMM-PR/VIES and GMS data. AWS rainfall data were used for various validation. General procedure is as follows; 1) Z-R relationship was made by the comparison of TRMM-PR and AWS data. 2) new algorithm was developed by the estimates from Z-R equation and TBB of VIRS. 3) rainfall was estimated through the substitution of GMS data for TBB of VIRS in the newly developed algorithm. Z-R relationship based on TRMM is $Z=303R^{0.72}$ with correlation coefficient 0.57. The newly developed algorithm is shown as correlation coefficient 0.67 and RMSE 17mm/hr. New algorithm shows the underestimating tendency in case of heavy rainfall event.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1456-1463
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• 2017

In recent times, IaaS (Infrastructure as a Services) have been rapidly evolving to allow developers to easily and efficiently access work in the server and network areas for development of a web of App based on cloud computing. In this study, we developed the collaborative image editing tool App based on Cloud-computing, by adopting AWS of representative company that develops IaaS. First, it is crucial to understand various situation conditions for representative infrastructure services: AWS, Azure and Google (GCP). This may have the effect of reducing manpower and development time, but as each company has different policy and technical support, we need a new study every time the environment changes of infrastructure services. We tried to develop a hybrid-App so that users with various devices can collaborate work each other by utilizing the infrastructure service AWS through the process of developing the image editing authoring tool based on the cloud computing. The future studies should continue about compatibility issues and support issues in order to minimize the problems of overseas infrastructure services, but we think that domestic cloud computing policies and developments should be urgently considered.

• Journal of Korea Water Resources Association
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• v.45 no.8
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• pp.743-753
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• 2012

AWS data can be used effectively to understand the rainfall characteristics in Korea. In spite of this advantage, AWS data have been used restrictively in flood control analysis and the study on water use analysis such as water balance assessment is very insufficient. In this study, AWS data are used to analyze spatial rainfall characteristics quantitatively and water balance assessment is performed based on AWS data. Water balance assessment is carried out from year 2002 to year 2010 considering water supply networks in Korea. The analysis shows that year 2009 is the driest year during 9 years (2002~2010) and the regions with low level water supply reliability are concentrated in the west coast of Jeonnam and the upper region of the Nakdong River. As a result, the regions that have a lack of available water resources such as the coastal and insular areas are vulnerable to droughts. Therefore, regional water supply and management plans are urgently needed. Additionally, AWS data, which consider rainfall characteristics of the coastal and insular areas, can be useful in water balance assessment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.3 no.1
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• pp.16-21
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• 2001

Regression models were obtained on the base of the correlation between Phytophthora blight incidence in red pepper and the microclimate data obtained from automated weather station (AWS) during 1997 and 1998. A computer program (PEPBLIGHT) was constructed based on the model that the R2 value is highest among regression models. This computer program uses the microclimate data from more than one AWS through the common dialogue box easy and it is able provide disease forecasting information. In addition, it could be applied far other diseases and converts the microclimate data of AWS to the input data for Statical Analysis System (SAS). PEPBLIGHT was first developed for the forecasting computer system of red pepper blight in Korea. PEPBLIGHT is operated on the MS Windows, so that it is easy to use.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.5
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• pp.25-33
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• 2013

All-wheel steering (AWS) system is applied to articulated vehicles to reduce turning radius. The swing-out suppression algorithm is applied to AWS ECU, a key component of AWS system. The swing-out suppression algorithm applied to AWS ECU has a problem when velocity of vehicle is changed. In this paper, new algorithm based on moving distance that solve velocity problem is proposed. The HILS simulation and the test articulated bus is used to validate algorithm.