• Journal of Korea Society of Industrial Information Systems
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• v.17 no.3
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• pp.105-114
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• 2012

Various RFID-based smart-walk systems have been developed for guiding disabled people. The system sends appropriate message whenever the disabled people arrived at a specific point. We propose universal design concept and optimization techniques for the smart-walk systems. Universal design concept can be adopted for supporting various kinds of disabled such as a blind person, a hearing-impaired person, or a foreigner in a system. It can be supported by storing appropriate messages set in the message database table depending on the kinds of the disabled. System optimization can be done by analyzing operational log(stream) data accumulated in the system. Useful information can be extracted by analyzing or mining the accumulated operational log data. We show various analysis results from the operational log data.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.175-184
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• 2012

This study was conducted to develop new mattress systems with vegetation base materials for protecting stream bank and rapid rehabilitation. Vegetation base materials are primarily compounded with fine soil, organic composts and peat moss as plant fibers, a water retainer and a soil improver. Peat moss can usually provide necessary natural fibers and organic materials in soil. Especially, peat moss can absorb up to 25 times its own weight in water and is therefore valued as a water retainer to prevent drying effect of vegetation base materials which can harm the growth of vegetation in mattresses. Normally mattress systems resist the lateral earth pressures or stream power by their own weight. Therefore, filled materials must have suitable weight, compressive strength and durability to resist the loading, as well as the effects of water and weathering. In this project, 100 to 200-mm clean, hard stones were basically specified, and about 50-mm rubbles were also used. Test application of new mattress system carried out in the stream bank of a small stream in the Gwangreung experimental forest, belonging to Korea Forest Research Institute (KFRI) in December 16th, 2006. As a result of the monitoring of vegetation coverage of test application plots (each plot size is 4 by 2 m), the coverage of all plots reached 100% in the end of May, 2007 (approximately 50 days passed after the first gemination of vegetation). The coverage of the plots using big hard stones and organic composts and the plots containing peat moss increased more rapidly. The results show that peat moss is effective to retain soil moisture and establish more sound environment for vegetation gemination.

• Journal of Internet Computing and Services
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• v.19 no.4
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• pp.1-6
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• 2018

In smart cities, data from various kinds of sensors are collected and processed to provide smart services to the citizens. Noise information services with noise maps using the collected sensor data from various kinds of ubiquitous sensor networks is one of them. This paper presents a research result which generates three dimensional (3D) noise maps in real-time for smart cities. To make a noise map, we have to converge many informal data which include big image data of geographical Information and massive sensor data. Making such a 3D noise map in real-time requires the processing of the stream data from the ubiquitous sensor networks in real-time and the convergence operation in real-time. They are very challenging works. We developed our own methodology for real-time distributed and parallel processing for it and present it in this paper. Further, we developed our own real-time 3D noise map generation system, with the methodology. The system uses open source softwares for it. Here in this paper, we do introduce one of our systems which uses Apache Storm. We did performance evaluation using the developed system. Cloud computing was used for the performance evaluation experiments. It was confirmed that our system was working properly with good performance and the system can produce the 3D noise maps in real-time. The performance evaluation results are given in this paper, as well.

• Economic and Environmental Geology
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• v.49 no.2
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• pp.105-120
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• 2016

Most of riverside in Korea, in case of application of water curtain cultivation (WCC) technique, has been inveterately suffering from the gradual drawdown of groundwater level and related shortage of water resources during the WCC peak time. We believe that the water resources issue in these riverside areas can be effectively solved when the interaction between groundwater and nearby surface water is well understood. To investigate the connection between stream and ground water, and the influence of stream water on the nearby aquifer, this study examined the water temperature and oxygen and hydrogen stable isotopic compositions. The study area is well-known strawberry field applying the WCC technique in Sangdae-ri, Gadeok-myon, Cheongju City, and the sampling was done from February 2012 through June 2014 for stream and ground water. Some groundwater wells near stream showed big temporal variations in water temperature, and their oxygen and hydrogen stable isotopes showed similar compositions to those of adjacent stream water. This indicates that the influence of stream water is highly reflected in the stable isotopic composition of groundwater. Four cross-sectional lines from stream to hillside were established in the study area to determine the spatial differences in water quality of wells. At the late stage of WCC in February to March, groundwater of wells in line with short cross-sectional length showed the narrow range of isotopic compositions; however, those in the long cross-sectional line showed a wide compositional range. It was shown that the influence of the stream water at the late WCC stage have reached to the distance of 160 to 165 m from stream line, which is equivalent to the whole length and one-third point in each short and long cross-sectional line, respectively. Therefore, the wide compositional range in the long cross-sectional lines was not only due to the influence of stream water, but apparently resulted from the change of relative impact of each groundwater supplying from two or more aquifers. In view of stable isotopic compositions, there seems to be three different aquifers in this study area, which is competing for dominance of water quality in wells at each period of WCC.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.513-523
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• 2015

A complex event processing system, becoming useful in real life domains, efficiently processes stream of continuous events like sensor data from IoT systems. However, those systems do not work well on some types of queries yet, so that programmers should be careful about that. For instance, they do not sufficiently provide detailed guide to choose efficient queries among the almost same meaning queries. In this paper, we propose an query preprocessing tool for event stream processing systems, which helps programmers by giving them the hints to improve performance whenever their queries fall in any possible bad formats in the performance sense. We expect that our proposed module would be a big help to increases productivity of writing programs where debugging, testing, and performance tuning are not straightforward.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.377-382
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• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.1-11
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• 2018

Recently, the volume of online shopping market continues to be fast-growing, that is important to provide customized service based on customer behavior evaluation analysis. The existing systems only provide analysis data on the profiles and behaviors of the consumers, and there is a limit to the processing in real time due to disk based mining. There are problems of accuracy and system performance problems to apply existing systems to web services that require real-time processing and analysis. Therefore, The system proposed in this paper analyzes the web click log streams generated in real time to calculate the concentration level of specific products and finds interested customers which are likely to purchase the products, and provides and intensive promotions to interested customers. And we verify the efficiency and accuracy of the proposed system.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.35-46
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• 2022

Recently, with the development of network technologies, as IoT and social network service applications have been actively used, a lot of graph stream data is being generated. In this paper, we propose a graph compression scheme that considers the stream graph environment by applying graph mining to the existing compression technique, which has been focused on compression rate and runtime. In this paper, we proposed Incremental frequent pattern based compression technique for graph streams. Since the proposed scheme keeps only the latest reference patterns, it increases the storage utilization and improves the query processing time. In order to show the superiority of the proposed scheme, various performance evaluations are performed in terms of compression rate and processing time compared to the existing method. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.651-659
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• 2014

With the popularization of big data environment, big data have been highlighted as a key information strategy to establish national spatial data infrastructure for a scientific land policy and the extension of the creative economy. Especially interesting from our point of view is the cadastral information is a core national information source that forms the basis of spatial information that leads to people's daily life including the production and consumption of information related to real estate. The purpose of our paper is to suggest the scheme of big data analytics with respect to the articles of cadastral resurvey project in order to approach cadastral information in terms of spatial data integration. As specific research method, the TM (Text Mining) package from R was used to read various formats of news reports as texts, and nouns were extracted by using the KoNLP package. That is, we searched the main keywords regarding cadastral resurvey, performing extraction of compound noun and data mining analysis. And visualization of the results was presented. In addition, new reports related to cadastral resurvey between 2012 and 2014 were searched in newspapers, and nouns were extracted from the searched data for the data mining analysis of cadastral information. Furthermore, the approval rating, reliability, and improvement of rules were presented through correlation analyses among the extracted compound nouns. As a result of the correlation analysis among the most frequently used ones of the extracted nouns, five groups of data consisting of 133 keywords were generated. The most frequently appeared words were "cadastral resurvey," "civil complaint," "dispute," "cadastral survey," "lawsuit," "settlement," "mediation," "discrepant land," and "parcel." In Conclusions, the cadastral resurvey performed in some local governments has been proceeding smoothly as positive results. On the other hands, disputes from owner of land have been provoking a stream of complaints from parcel surveying for the cadastral resurvey. Through such keyword analysis, various public opinion and the types of civil complaints related to the cadastral resurvey project can be identified to prevent them through pre-emptive responses for direct call centre on the cadastral surveying, Electronic civil service and customer counseling, and high quality services about cadastral information can be provided. This study, therefore, provides a stepping stones for developing an account of big data analytics which is able to comprehensively examine and visualize a variety of news report and opinions in cadastral resurvey project promotion. Henceforth, this will contribute to establish the foundation for a framework of the information utilization, enabling scientific decision making with speediness and correctness.