• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.45-57
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• 2007

Recently, the development of sensor devices has accelerated researches on advanced technologies like Wireless Sensor Networks. Moreover, spatial sensors using GPS lead to the era of the Ubiquitous Computing Environment which generally uses spatial information and non-spatial information together. In this new era, a real-time processing system for spatial sensor data is essential. In this reason, new data processing systems called DSMS(Data Stream Management System) are being developed by many researchers. However, since most of them do not support geometry types and spatial functions to process spatial sensor data, they are not suitable for the Ubiquitous Computing Environment. For these reasons, in this paper, we designed and implemented a spatial DSMS by extending STREAM which stands for STanford stREam datA Manager, to solve these problems. We added geometry types and spatial functions to STREAM in order to process spatial sensor data efficiently. In addition, we implemented a Spatial Object Manager to manage shared spatial objects within the system. Especially, we implemented the Simple Features Specification for SQL of OGC for interoperability and applied algorithms in GEOS to our system.

• Journal of Korea Water Resources Association
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• v.45 no.1
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• pp.1-13
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• 2012

Various input data required for water quality modeling have considerable impacts on modeling results and relevant analysis due to the absence of data standardization and lack of data accuracy. With this in mind, this study mainly focused on the designing Korean Reach File for more effective water quality modeling through the supply of database composed with accurate hydraulic and hydrologic data. The Korean Reach File is the hydraulic database with the locational information of individual reaches, and each reach represents the stream reach of homogeneous hydraulic characteristics. In detail, it has reach code designating each stream reach, and topological information including catalog unit, segment, marker and index. It was also designed considering linkage of existing codes such as stream name and stream code. The devised reach code was implemented to Kyungan River at the City of Gwangju of Kyunggi Province and the results showed that the reach code could effectively support the input database integrating basic numerous data required for water quality modeling based on a criterion as well as easier linkage and utilization with existing database. In addition, more systematic water quality management was enabled through the linkage of existing data such as treatment facilities, pollutant data, and management institutes using the reach codes defined for each stream section. In the future, more efforts need to be made to adopt the reach code as the national standard data thereby enabling utilization of numerous relevant database through the assigning of reach code to individual stream reaches nationwide.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.53-59
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• 2016

Recently, huge stream data have been generated in real time from various applications such as wireless sensor networks, Internet of Things services, and social network services. For this reason, to develop an efficient method have become one of significant issues in order to discover useful information from such data by processing and analyzing them and employing the information for better decision making. Since stream data are generated continuously and rapidly, there is a need to deal with them through the minimum access. In addition, an appropriate method is required to analyze stream data in resource limited environments where fast processing with low power consumption is necessary. To address this issue, the sliding window model has been proposed and researched. Meanwhile, one of data mining techniques for finding meaningful information from huge data, pattern mining extracts such information in pattern forms. Frequency-based traditional pattern mining can process only binary databases and treats items in the databases with the same importance. As a result, frequent pattern mining has a disadvantage that cannot reflect characteristics of real databases although it has played an essential role in the data mining field. From this aspect, high utility pattern mining has suggested for discovering more meaningful information from non-binary databases with the consideration of the characteristics and relative importance of items. General high utility pattern mining methods for static databases, however, are not suitable for handling stream data. To address this issue, sliding window based high utility pattern mining has been proposed for finding significant information from stream data in resource limited environments by considering their characteristics and processing them efficiently. In this paper, we conduct various experiments with datasets for performance evaluation of sliding window based high utility pattern mining algorithms and analyze experimental results, through which we study their characteristics and direction of improvement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.690-696
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• 2004

Advanced Television Systems Committee (ATSC) -A/90, which is a standard for terrestrial data transmission in Korea, defines synchronized data that has a strong timing association with a separate Program Element. It is classified as synchronized streaming data that is carried in packetized elementary stream (PES) packets or a synchronized non-streaming data that shall be carried in digital storage media command and control (DSM-CC) section. In this paper, we study the design and verification of synchronized streaming data processing algorithm based on ATSC -A/90. We designed a parser and a player for the algorithm development. The received PES packet including synchronized streaming data is parsed in the parser. The parsed synchronized streaming data is synchronized and displayed by player. Finally, we ascertained that STB was working properly with MPEG-2 transport stream (TS) containing synchronized streaming data, as the proposed algorithm is implemented on a set-top box.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.103-114
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• 2012

The purpose of this research is classifying stream into different types depending on various factor from the perspective of stream corridor restoration and using it as basic data, which are used to consider efficient management and planning for the healthy stream according to the characteristic by types. In this study, 130 points of location of the Nakdong river basin which consist of various geographic factors have been chosen and hierarchical cluster analysis has been carried out in these points by using biological and physiochemical factors whose health can be considered to be predicted and evaluated. As a result of cluster analysis, there were three divided types. Type A whose biology and water quality are considered the best was the highest in forest area percentage so that it was classified into natural stream. Type B was classified into a rural region stream with a mixture of urban and agricultural region. Type C, with the most damaged water quality and biology health had the most urban region surface area and was named as urban region stream. Moreover, an overall restoration strategy according to characteristic by stream types was set. By the results of correlation analysis on factors, water quality showed a high correlation with biological properties and was affected by surrounding land usage. In evaluation of streams, it proves the need to consider not only other habitat's geographical and biological factors but also the water quality and land usage factors. There needs to be further research on stream ecosystem functionality factors and structural aspects by using a more objective and total evaluation result in selecting additional index and various other specific classification methods by stream types and its restoration strategies.

• Journal of Korean Society on Water Environment
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• v.36 no.5
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• pp.364-372
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• 2020

The "Master Plan for the Revitalization of Water in the Nakdong River" is designed for the fundamental improvement of water quality in the Nakdong River. The water quality and flow of the Nakdong River system tributaries was monitored in this study. Among the living environmental standard parameters of 195 rivers, BOD (Biochemical oxygen demand), T-P (Total phosphorus) and TOC (Total organic carbon) were assessed to analyze the water quality from 2012 to 2019. We examined the role of TOC. It was found that 12 rivers exceeded the water quality of the second grade (3.0 mg/L BOD standard, 0.1 mg/L T-P standard, 4.0 mg/L TOC standard) based on BOD and T-P concentrations: the Gumi stream, Gisegok stream, Yongha stream, Yongho stream, Changnyeong stream, Gajwa stream, Gwangok stream, Yeongsan stream, Toerae stream, Hwapo stream, Sangnam stream and Hogye stream. These rivers require strategies to improve the quality of the Nakdong River. Based on the ongoing project, it is possible to supplement the "Master Plan for the Revitalization of Water in the Nakdong River" and manage it after verifying it as a component of people's life and therefore used to establish water quality control measures.

• Korean Journal of Ecology and Environment
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• v.42 no.4
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• pp.502-509
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• 2009

In this study a total of 27 stream sites, at 1 km intervals, were monitored for simple physicochemical water characteristics, land coverage patterns, and stream environment characteristics using the Habitat-riparian Indexing System (HIS), in the Yangsan Stream. The HIS has been tested in previous research, resulting in some identification of advantages in the application to the stream ecosystems data. Even though reliable stream environment characterization was possible using HIS, there was no information about the application of this tool to present continuity of environmental changes in stream systems. Also the necessity was raised to compare the results of HIS application with land coverage information in order to provide useful information in management strategy development. The monitoring results of this study showed that changes of environmental degradation were well represented by HIS. Especially, stream environment degradation due to construction was relatively well reflected in the HIS monitoring results, and the main causality of Yangsan Stream degradation was expansion of the urbanized area. In addition, there were significant relationships between the HIS scores and land coverage information. Therefore, it is necessary to prepare appropriate options in controlling or managing the expansion of the industrialized areas in this stream basin in order to improve the stream environment. For this purpose, ensemble utilization of HIS results, water quality, and geographical information, resulting in integration with remote sensing processes can be possible.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.561-566
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• 2001

This study is the analysis of hydraulic characteristic for stream diversion reach by numerical model test. Through it we can provide the basis data in flood, and in grasping stream flow characteristics. Analysis of hydraulic characteristics in Seoknam stream were implemented by using computer model HEC-RAS(one-dimensional model) and RMA2(two-dimensional finite element model). As a result we became to known that RMA2 to simulate left, main channel, right in stream is more effective method in analysing flow in channel bends, steep slope, complex bed form effect stream flow characteristics, than HEC-RAS.

• Korean Journal of Environment and Ecology
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• v.29 no.2
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• pp.292-303
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• 2015

The objective of this study is to evaluate the spatial restoration of Hampyeong Stream and to analyze the determinants of demand for the multi-functionalities of the stream. A Contingent Valuation Method (CVM) was used to estimate the multi-functional public benefits of restored stream area, and major determinants were scrutinized by establishing a demand model. The research data was collected by conducting a survey intended for Hampyeong's local residents, resulting in 284 valid samples. In terms of determinants that affect willingness to pay (WTP), 'physical factor of waterfront area' and 'experience factor of stream space' showed a significantly positive influence on WTP. As a result of applying a double-bounded CVM, the willingness to pay for the restored Hampyeong Stream area indicated a potential contribution of 22,523 won (17,362~27,459 won, 95% confidence interval). When multiplying the number of households in Hampyeong-gun, the total annual value of Hampyeong Stream spatial restoration is approximately 302million won.