• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.671-678
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• 2019

The semantic information provided through the semantic-based IoT system will produce new high value-added products that are completely different from what we have known and experienced. From this point of view, the key issue of current IoT technology and applications is the development of an intelligent IoT platform architecture. The proposed system collects the IoT data of the sensors from the cloud computer, converts them into RDF, and annotates them with semantics. The converted semantic data is shared and utilized through the ontology repository. We use KT's IoTMakers as a cloud computing environment, and the ontology repository uses Jena's Fuseki server to express SPARQL query results on the web using Daum Map API and Highcharts API. This gives people the opportunity to access the semantic IoT mash-up service easily and has various application possibilities.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1030-1036
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• 2020

The DSRC method currently in use has a limitation in providing various ITS services by short-distance wireless communication. Therefore, the WAVE/DSRC hybrid wireless platform, which was developed by applying WAVE technology in-house, improved the data transmission speed and greatly expanded the transmission range. The summary H/W and S/W technologies are summarized in the text. In this paper, various services such as BSM, SPAT, MAP, and road video information related to ITS services have been implemented, and various tests are conducted based on scenarios considering the environment in the actual field by utilizing the previously developed WAVE/DSRC composite wireless platform. Through this emulation process in the real field, we were able to verify the excellence of the WAVE/DSRC composite wireless platform once again and predict the usefulness and potential of development services in real field operations.

• Atmosphere
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• v.26 no.1
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• pp.111-126
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• 2016

In the numerical weather model, surface properties can be defined by various parameters such as terrain height, landuse, surface albedo, soil moisture, surface emissivity, roughness length and so on. And these parameters need to be improved in the Seoul metropolitan area that established high-rise and complex buildings by urbanization at a recent time. The surface roughness length map is developed from digital elevation model (DEM) and it is implemented to the high-resolution numerical weather (WISE-WRF) model. Simulated results from WISE-WRF model are analyzed the relationship between meteorological variables to changes in the surface roughness length. Friction speed and wind speed are improved with various surface roughness in urban, these variables affected to temperature and relative humidity and hence the surface roughness length will affect to the precipitation and Planetary Boundary Layer (PBL) height. When surface variables by the WISE-WRF model are validated with Automatic Weather System (AWS) observations, NEW experiment is able to simulate more accurate than ORG experiment in temperature and wind speed. Especially, wind speed is overestimated over $2.5m\;s^{-1}$ on some AWS stations in Seoul and surrounding area but it improved with positive correlation and Root Mean Square Error (RMSE) below $2.5m\;s^{-1}$ in whole area. There are close relationship between surface roughness length and wind speed, and the change of surface variables lead to the change of location and duration of precipitation. As a result, the accuracy of WISE-WRF model is improved with the new surface roughness length retrieved from DEM, and its surface roughness length is important role in the high-resolution WISE-WRF model. By the way, the result in this study need various validation from retrieved the surface roughness length to numerical weather model simulations with observation data.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.167-177
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• 2015

This study was conducted to establish an inventory and propose conservation strategies for 'village wetlands' in Asan city, Korea, using GIS. As results, the village wetlands are defined as such places as 'palustrine' wetland, village embankment, agricultural reservoir or small reservoirs located in or near the village and related to everyday life or farming. Firstly 807 provisional village wetlands(draft) were identified in Asan by using Arc-GIS 10.1, then 196 wetlands(final) were defined finally as village wetlands and listed the inventory of Asan Village Wetlands after being validated through office works and field survey. The office works analyzed minimum area(greater than $625m^2$), satellite images, the Korea Land Information System, land use map and land coverage map. To evaluate the function and conservation values, the 37 wetlands were selected for detailed surveying and function assessment based on the following criteria : 1) doubled code both wetland and reservoir at digital map, 2) located less than 100m from village and 3) ecologically connected to such ecological resources as seaside mudflats, mountains and green area and ecological passages for small size wildlifes. As the result of the wetland function assessments by the RAM method, 7 wetlands were found to have 'high' wetland function (conservation) 18 wetlands were 'medium' (enhancement) and 12 wetlands were 'low' (restoration or enhancement). Enhancing biodiversity and ecosystem services through ecological management of wetlands in Asan and connecting with the Ecological Natural Degree were proposed.

• The Journal of Bigdata
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• v.1 no.2
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• pp.1-8
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• 2016

User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.9-18
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• 2008

Web-services have originally been devised to share information as open services. In connection with it, hacking incidents have surged. Currently, Web-log analysis plays a crucial clue role in detecting Web-hacking. A growing number of cases are really related to perceiving and improving the weakness of Web-services based on Web-log analysis. Such as this, Web-log analysis plays a central role in finding out problems that Web has. Hence, Our research thesis suggests Web-DoS-hacking detective technique In the process of detecting such problems through SOM algorithm, the emergence frequency of BMU(Best Matching Unit) was studied, assuming the unit with the highest emergence frequency, as abnormal, and the problem- detection technique was recommended through the comparison of what's called BMU as input data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.960-966
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• 2012

It is prevalent to gather the location information from GPS, WiFi and etc, and therefore LBSNS (Location-Based SNS) has increased rapidly (such as location-augmented Twitter services). The message created from LBSNS include the specific area of interests which the message is created in or mentions. It is easy to propagate the location-based information of LBSNS by adapting the retweet function which is efficient way to propagate the message in tweeter. In this paper, we have defined the smart retweet as a automatic retweet function for efficient propagating the messages which is geo-tagging the location of interests. We have designed the smart retweet system based on the tweeter system. The user could specify the area of interests and build the social networking among the users which have interested in common area. The smart retweet system have been implemented by mesh-up services based on Open-API of trweeter and google map. It is expected that the smart retweet service proposed in this paper makes easy sharing of the location-based interesting information.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.266-273
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• 2005

Data mining techniques enable us to generate useful information for decision support from the data sources which are generated and accumulated in the process of routine organizational management activities. College administration system is a typical example that produces a warehouse of student records as each and every student enters a college and undertakes the curricular and extracurricular activities. So far, these data have been utilized to a very limited student service purposes, such as issuance of transcripts, graduation evaluation, GPA calculation, etc. In this paper, we utilize Holland career search test results, TOEIC score, course work list, and GPA score as the input for data mining and generation the student advisory information. Factor analysis, AHP(Analytic Hierarchy Process), artificial neural net, and CART(Classification And Regression Tree) techniques are deployed in the data mining process. Since these data mining techniques are very powerful in processing and discovering useful knowledge and information from large scale student databases, we can expect a highly sophisticated student advisory knowledge and services which may not be obtained with the human student advice experts.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.