• Journal of Soil and Groundwater Environment
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• v.28 no.2
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• pp.12-29
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• 2023

Conceptual site model (CSM) development and enhancement for contaminated sites assists in identifying data gaps during the site investigation process. In this study, CSM was developed and enhanced for a contaminated site in Korea as a case study. Site Y was scrutinized four times previously. The site profiles for each scrutiny were reorganized based on the scrutiny reports, and the relevant data was utilized to develop and enhance CSMs. CSM for the first investigation was developed in various forms including table, flowchart, diagram, and narrative formats. CSM was enhanced in a stepwise manner by incorporating the updated profile information obtained in next investigation to existing CSM. The hypothetical data gap analysis between each investigation step was established to meet the purpose of the follow-up investigation. This case study showed that CSM is a useful tool to identify the history and current status of contaminated sites and thereby help in planning supplementary investigations for better site characterization.

• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.306-315
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• 2022

In this study, long-term measurement data were applied to the LOADEST model and used as an analysis tool to identify and interpret trends in pollution load. The LOADEST model is a regression equation-based pollution load estimation program developed by the United States Geological Survey (USGS) to estimate the change in the pollution load of rivers according to flow rate and time and provides 11 regression equations for pollution load evaluation. As a result of simulating the Gwangjuchen2, Pungyeongjeongchen, and Pyeongdongchen in the Yeongbon B unit basin in the middle and upper reaches of the Yeongsan River with the LOADEST model using water quality and flow measurement data, lower values were observed for the Gwangjuchen2 and Pyeongdongchen, whereas the Pungyeongjeongchen had higher values. This was judged to be due to the characteristics of the LOADEST model related to data continuity. According to the parameters estimated by the LOADEST model, pollutant trends were affected by increases in the flow. In addition, variability increased with time, and BOD and T-P were affected by the season. Thus, the LOADEST model can contribute to water quality management as an analytical tool for long-term data monitoring.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.139-146
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• 2012

Data Mining is widely used to discover knowledge in many fields. Although there are many methods to discover association rule, most of them are based on frequency-based approaches. Therefore it is not appropriate for stream environment. Because the stream environment has a property that event data are generated continuously. it is expensive to store all data. In this paper, we propose a new method to discover association rules based on stream environment. Our new method is using a variable window for extracting data items. Variable windows have variable size according to the gap of same target event. Our method extracts data using COBJ(Count object) calculation method. FPMDSTN(Frequent pattern Mining over Data Stream using Terminal Node) discovers association rules from the extracted data items. Through experiment, our method is more efficient to apply stream environment than conventional methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1859-1867
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• 2021

Multi LiDAR sensors are being mounted on autonomous vehicles, and a system to multi LiDAR sensors data is required. When sensors data is transmitted or processed to the main processor, a huge amount of data causes a load on the transport network or data processing. In order to minimize the number of load overhead into LiDAR sensor processors, only semantic data is transmitted through data comparison between frames in LiDAR data. When data from 4 LiDAR sensors are processed in a static environment without moving objects and a dynamic environment in which a person moves within sensor's field of view, in a static experiment environment, the transmitted data reduced by 89.5% from 232,104 to 26,110 bytes. In dynamic environment, it was possible to reduce the transmitted data by 88.1% to 29,179 bytes.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.125-128
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• 2001

Nowadays, Internet users are widespread internationally. Fallowing the users requirements, server has to transfer real-time multimedia data to many clients. Multicast can significantly reduce the system overhead and the network resource waste, so it supports efficient mechanism when server has to transfer same data to many clients. We can deliver multimedia data transfer in real-time using Patching Algorithm which has no delay for service request. And multicast algorithm can support different network bandwidth using Receiver driven Layered Multicast under heterogeneous environment network. The purpose of this paper is to suggest an algorithm that can create new multicast group adequately and transfer real-time multimedia data efficiently under heterogeneous environment.

• International Journal of Contents
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• v.14 no.1
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• pp.34-38
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• 2018

With the rapid growth of genomic data, new requirements have emerged that are difficult to handle with big data storage and analysis techniques. Regardless of the size of an organization performing genomic data analysis, it is becoming increasingly difficult for an institution to build a computing environment for storing and analyzing genomic data. Recently, cloud computing has emerged as a computing environment that meets these new requirements. In this paper, we analyze and compare existing distributed and parallel NGS (Next Generation Sequencing) analysis based on cloud computing environment for future research.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.23-32
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• 2013

The purpose of this study is to make effective mobile grid considered general environment, which can be summarized as irregular mobility, service exploration, data sharing, variety of machines, limit to the battery duration, etc. The data was extracted from the Dartmouth College. We analysed mobile use pattern of a specific group and applied pattern using hybrid method. As a result, we could adjust infra usage effectively and appropriately and cost cutting and increase satisfaction of user. In this study, by applying weighting method based on access time interval, we analysed use pattern added time variation with association rule during users in mobile grid environment. We proposed more stable way to manage patterns in a mobile grid environment that is being used as a hybrid form to process the data value received from the server in real time. Further studies are needed to get appropriate use pattern by group using use patterns of various groups.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.3-5
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• 2007

Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.61-71
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• 2014

Social networking services have changed the way people communicate. Rapid growth of information generated by social networking services requires effective search methods to give useful results. Over the last decade, social search methods have rapidly evolved. Traditional techniques become unqualified because they ignore social relation data. Existing social recommendation approaches consider social network structure, but social context has not been fully considered. Especially, the friend recommendation is an important feature of SNSs. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose a levelized data processing method for social search in ubiquitous environment. We study previous researches about social search methods in ubiquitous environment. Our method is a new paradigm of levelelized data processing method which can utilize information in social networks, using location and friendship weight. Several experiments are performed and the results verify that the proposed method's performance is better than other existing method.

• Journal of Information Technology Applications and Management
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• v.13 no.2
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• pp.115-126
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• 2006

Recently, flash memories are one of best media to support portable computer's storages in mobile computing environment. We propose a new transaction recovery scheme for a flash memory database environment which is based on a flash media file system. We improved traditional shadow paging schemes by reusing old data pages which are supposed to be invalidated in the course of writing a new data page in the flash file system environment. In order to reuse these data pages, we exploit deferred cleaning list structure in our flash memory shadow paging (FMSP) scheme. FMSP scheme removes the additional storage overhead for keeping shadow pages and minimizes the I/O performance degradation caused by data page distribution phenomena of traditional shadow paging schemes. We also propose a simulation model to show the performance of FMSP. Based on the results of the performance evaluation, we conclude that FMSP outperforms the traditional scheme.