• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.1-13
• /
• 2018

Both Platform as a Service (PaaS) as one of the cloud computing service models and the e-government (e-Gov) standard framework from the Ministry of the Interior and Safety (MOIS) provide developers with practical computing environments to build their applications in every web-based services. Web application developers in the geo-spatial information field can utilize and deploy many middleware software or common functions provided by either the cloud-based service or the e-Gov standard framework. However, there are few studies for their applicability and performance in the field of actual geo-spatial information application yet. Therefore, the motivation of this study was to investigate the relevance of these technologies or platform. The applicability of these computing environments and the performance evaluation were performed after a test application deployment of the spatial image processing case service using Web Processing Service (WPS) 2.0 on the e-Gov standard framework. This system was a test service supported by a cloud environment of Cloud Foundry, one of open source PaaS cloud platforms. Using these components, the performance of the test system in two cases of 300 and 500 threads was assessed through a comparison test with two kinds of service: a service case for only the PaaS and that on the e-Gov on the PaaS. The performance measurements were based on the recording of response time with respect to users' requests during 3,600 seconds. According to the experimental results, all the test cases of the e-Gov on PaaS considered showed a greater performance. It is expected that the e-Gov standard framework on the PaaS cloud would be important factors to build the web-based spatial information service, especially in public sectors.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1125-1139
• /
• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• Journal of Korean Home Economics Education Association
• /
• v.32 no.4
• /
• pp.149-170
• /
• 2020

The purpose of this study was to develop and evaluate a Smart learning-based middle school home economics education plan to improve the online home economics education classes. The educational plan in this study was completed through the process of analysis, design, development, and evaluation. The results of this study are as follows. First, as a result of analyzing consumer life units in the middle school textbooks based on 2015-revised curriculum, Smart learning activities were presented in only two out of the 12 textbooks analyxed. Second, a Smart learning-based middle school home economics education plan was developed in this study with the following characteristics: the topics and contents are structured so that to help learners actively engage in the teaching and learning activities; the education plan to reflects various media and current issues that learners may be interested in; the lesson plans were structured with the premise of online classes; softwares that enable real-time discussion and collaboration are used; and the evaluation method are composed of online activities. Third, the expert evaluation scores for the educational plan and activity materials developed were 4.52 (5-point Likert scale), when averaged across subject, goal, content, teaching/learning activity, and evaluation, and the overall content validity index(CVI) was 0.95. The adequacy of execution, benefit, attractiveness, usefulness, and feasibility were highly with an average of 4.62. Based on the experts' comments, the education plan and activity materials were revised and completed. This study is meaningful in that it developed teaching and learning activities based on online classes after the COVID-19 outbreak, overcoming the limitations of offline classes. It has implications for face-to-face home economics classes due to COVID-19, as it suggests ways to blend online and offline teaching/learning activities depending on the situation.