• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.573-578
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• 2019

This paper applied to the Korean Lesson using PBL(Problem-Based Learning) based on Google Classroom for Mongolians. Recently, Mongolians trying to learn Korean because of Korean wave. This study aims to develop the online problem-based learning model as a way to develop the creative problem-solving ability of Mongolians who want to learn Korean. We applied 3 problems for 9 weeks. This study shows that the participants experienced the effectiveness of Google Classroom and PBL in many ways, 93% of the participants reported that Google Classroom and PBL helped them to learn Korean easily and interesting distance learning model, 90% of the participants prefer to explore Googlish programs and online learning, 85% of them said that increased interaction others in online environment easily. 100% of them said that thankful for learning Korean with Online tutor anytime on Google Classroom. Truly, 86% of them said PBL was hard to generate and understand it because very new instruction for them and working with team in online learning environment. The study showed that members of Korean Lesson experienced various effects such as understanding of learning contents, understanding of cooperative learning, practical experience, creative problem solving ability, presentation skill, communication ability, self - directed learning ability, self - confidence through Google Classroom based PBL.

• The Mathematical Education
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• v.52 no.4
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• pp.531-547
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• 2013

The purpose of the study is to examine how effects of activities using Google SketchUp on students' spatial ability and 3D geometric thinking in measuring the volume of solid figures. By comparing the results from pre- and post-tests between the experimental group and control group, we found that activities using Google SketchUp help students improve their spatial ability in the spatial orientation and visualization. In addition, more than half students in the experimental group moved from level 4 up to level 7 in thinking process of measuring the volume in terms of Battista(2004)'s levels. This study suggests that the instruction with Google SketchUp can help to improve students' spatial ability and 3D geometric thinking in the regular class in middle school. In addition, SketchUp can be an advanced technological tool to support students' self-directed learning, which create an efficient educational environment and a great opportunity to learn geometry in an effective manner.

• Journal of the Korean Society for information Management
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• v.27 no.3
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• pp.307-323
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• 2010

The amount of online scholarly information rapidly expands in numerous resources, while user behavior demands single search box interface like Google Scholar. Despite scholarly values of e-resources libraries provide, users consider Google Scholar as the most efficient research tool attracted by its speed, simplicity, ease of use, and convenience. Characteristics of Metasearch System compared with Google Scholar are analyzed from perspectives of the interface and e-resource. Based on usage statistics of Metasearch System along with a link resolver in one academic library, e-resource accessibility patterns and information seeking behaviors of subject-specific areas are investigated for electronic information services.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.53-59
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• 2010

Android that was made by Google and Open Handset Alliance is the open source software toolkit for mobile phone. In a few years, Android will be used by millions of Android mobile phones and other mobile devices, and become the main platform of application developers. In this paper, we develop an application contents Booky based on Google Android flatform by using Webview merits and Google search engine. The features of the developed content are as follows. First, a mobile-based Web browser which has an advanced screen resolution and can support more faster viewer than normal web browser as it reduces the amount of data transmission. Second, efficient E-book search and reading functionality. In the performance evaluation, we show the results of simulation using AVD(Android Virture Device).

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.43-50
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• 2017

These days voice models of speech recognition software are sophisticated enough to process the natural speech of people without any previous training. However, not much research has reported on the use of speech recognition tools in the field of pronunciation education. This paper examined Google speech recognition of a short English paragraph produced by Korean college students in clear and casual speech styles in order to diagnose and resolve students' pronunciation problems. Thirty three Korean college students participated in the recording of the English paragraph. The Google soundwriter was employed to collect data on the word recognition rates of the paragraph. Results showed that the total word recognition rate was 73% with a standard deviation of 11.5%. The word recognition rate of clear speech was around 77.3% while that of casual speech amounted to 68.7%. The reasons for the low recognition rate of casual speech were attributed to both individual pronunciation errors and the software itself as shown in its fricative recognition. Various distributions of unrecognized words were observed depending on each participant and proficiency groups. From the results, the author concludes that the speech recognition software is useful to diagnose each individual or group's pronunciation problems. Further studies on progressive improvements of learners' erroneous pronunciations would be desirable.

• International Journal of Contents
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• v.8 no.1
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• pp.55-60
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• 2012

Most Korean and overseas major portal sites include map servers to provide map services, and offer open APIs to allow their users to make use of maps or spatial information directly. At the early design stage, geographic spatial data do not tend to require high accuracy, and thus there would be no problem using data which have been obtained and then utilized through map servers provided by portal sites. This study has chosen the shortest route between starting point and destination, using GIS techniques. Moreover, for the chosen route, it also has calculated the elevation for the cross-section, using Google map and GPS measurements. This study aims to create APIs, which can extract vertical profile of routes from the Google Map server, by using JAVA, and to compare centerline profile results obtained by GPS(Global Positioning System) to explore their utilize abilities. The result demonstrated a height error of 0.5 to 1 m, compared to the GPS results, but they were mutually satisfactory. In short, the data extracted in this study are useful for centerline profile drawings in selecting routes, such as streets, Olle roads, and bike lanes.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.341-344
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• 2007

A major obstacle to classify and validate Land Cover maps is the high cost of generating reference data or multiple thematic maps for subsequent comparative analysis. In case of inaccessible area such as North Korea, the high resolution satellite imagery may be used as in situ data so as to overcome the lack of reliable reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird (0.6m) of North Korea obtained from Google Earth data provided thru internet. Monthly NDVI images of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes; coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water and built-up area. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional in situ data collection on the site where the accessibility is severely limited.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.1075-1081
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• 2016

The big data analysis has received much attention from the researchers working in various fields because the big data has a great potential in detecting or predicting future events such as epidemic outbreaks and changes in stock prices. Reflecting the current popularity of big data analysis, many authors have proposed methods tracking influenza epidemics based on internet-based information. The recently proposed 'autoregressive model using Google (ARGO) model' (Yang et al., 2015) is one of those influenza tracking models that harness search queries from Google as well as the reports from the Centers for Disease Control (CDC), and appears to outperform the existing method such as 'Google Flu Trends (GFT)'. Although the ARGO predicts well the outbreaks of influenza, this study demonstrates that a classical seasonal autoregressive integrated moving average (SARIMA) model can outperform the ARGO. The SARIMA model incorporates more accurate seasonality of the past influenza activities and takes less input variables into account. Our findings show that the SARIMA model is a functional tool for monitoring influenza epidemics.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.181-188
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• 2010

This paper proposes 3D visualization systems for the real-time situation awareness and a state information of the aircraft. This system was embodied with OpenGL and the Google Earth of web base using situation data of the aircraft. The existing system has problem which speed decrease and visible restricted map because massive data of terrain and satellite photo. This system is supports the visualization tool which is economic and entire area for a real-time situation awareness with minimum flight information using Open-API of the Google Earth. Also provides a visible convenience to expansion-view using multiple location information. This research result could be used to system for the situation awareness of the aircraft from web environment.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.483-491
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• 2007

One of the major obstacles to classify and validate Land Cover maps is the high cost of acquiring reference data. In case of inaccessible areas such as North Korea, the high resolution satellite imagery may be used for reference data. The objective of this paper is to investigate the possibility of utilizing QuickBird high resolution imagery of North Korea that can be obtained from Google Earth data via internet for reference data of land cover classification. Monthly MODIS NDVI data of nine months from the summer of 2004 were classified into L=54 cluster using ISODATA algorithm, and these L clusters were assigned to 7 classes - coniferous forest, deciduous forest, mixed forest, paddy field, dry field, water, and built-up areas - by careful use of reference data obtained through visual interpretation of the high resolution imagery. The overall accuracy and Kappa index were 85.98% and 0.82, respectively, which represents about 10% point increase of classification accuracy than our previous study based on GCP point data around North Korea. Thus we can conclude that Google Earth may be used to substitute the traditional reference data collection on the site where the accessibility is severely limited.