• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.3
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• pp.73-85
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• 2002

The purpose of this study was to develop prediction models for plant species abundance by stream restoration. Generally the stream plant is affected by stream gemophology. So in this study, the relationship between the vegetation abundance and stream gemophology was developed by multiple regression analysis. The stream characteristics utilized in this study were longitudinal slope, transectional slope, micro-landforms through the longitudinal direction, riparian width and geometric mean diameter and biggest diameter of bed material, and cumulated coarse and fine sand weight portion. The Pyungchang River with mountainous watershed and the Kyungan stream and the Bokha stream in the agricultural region were selected and vegetation species abundance and stream characteristics were documented from the site at 2~3km intervals from the upper stream to the lower. The Models for predicting the vegetation abundance were developed by multiple regression analysis using SPSS statistics package. The linear relationship between the dependant(species abundance) and independant(stream characteristics) variables was tested by a graphical method. Longitudinal and transectional slope had a nonlinear relationship with species abundance. In the next step, the independance between the independant variables was tested and the correlation between independant and dependant variables was tested by the Pearson bivariate correlation test. The selected independant variables were transectional slope, riparian width, and cumulated fine sand weight portion. From the multiple regression analysis, the $R^2$for the Pyungchang river, Kyungan stream, Bokga stream were 0.651, 0.512 and 0.240 respectively. The natural stream configuration in the Pyungchang river had the best result and the lower $R^2$for Kyunan and Bokha stream were due to human impact which disturbed the natural ecosystem. The lowest $R^2$for the Bokha stream was due to the shifting sandy bed. If the stream bed is fugitive, the prediction model may not be valid. Using the multiple regression models, the vegetation abundance could be predicted with stream characteristics such as, transection slope, riaparian width, cumulated fine sand weigth portion, after stream restoration.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.73-82
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• 2017

Recently in-memory data stream processing has been actively applied to various subjects such as query processing, OLAP, data mining, i.e., frequent item sets, association rules, clustering. However, finding regular periodic patterns of events in an infinite data stream gets less attention. Most researches about finding periods use autocorrelation functions to find certain changes in periodic patterns, not period itself. And they usually find periodic patterns in time-series databases, not in data streams. Literally a period means the length or era of time that some phenomenon recur in a certain time interval. However in real applications a data set indeed evolves with tiny differences as time elapses. This kind of a period is called as a pseudo-period. This paper proposes a new scheme called FPMH (Finding Periods using Multiple Hash functions) algorithm to find such a set of pseudo-periods over a data stream based on multiple hash functions. According to the type of pseudo period, this paper categorizes FPMH into three, FPMH-E, FPMH-PC, FPMH-PP. To maximize the performance of the algorithm in the data stream environment and to keep most recent periodic patterns in memory, we applied decay mechanism to FPMH algorithms. FPMH algorithm minimizes the usage of memory as well as processing time with acceptable accuracy.

• Journal of Korean Society of Forest Science
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• v.89 no.3
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• pp.297-305
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• 2000

This research was conducted to analyze the factors influenced on stream water quality pollution in the northeastern part of Puk'ansan National Park from July, 1998 to November, 1999. The number of visitor and the percentage of the amount of $Cl^-$ resulted in the increase of electrical conductivity, which affected on pollution of the stream water quality. The relationships between those factors should be statistical significance at the 5% level in multiple regression. The multiple regression equations for the percentage of dissolved oxygen at the stream water quality showed that dissolved oxygen and water temperature had statistical significance at the 1% level. The multiple regression equations for the amount of $Cl^-$ at the stream water quality showed that electrical conductivity, the amount of cation($K^+$, $Na^+$), the amount of $SO_4{^{2-}}$, total amount of ion, the percentage of the amount of $Cl^-$, and the percentage of the amount of $SO_4{^{2-}}$ had statistical significance at the 5% and 1% level. Also, The multiple regression equations for the amount of $NO_3{^-}$ at the stream water quality showed that the amount of cation($Na^+$, $Ca^{2+}$), the amount of $SO_4{^{2-}}$, the percentage of the amount of $Cl^-$, and the percentage of the amount of $NO_3{^-}$ had statistical significance at the 5% and 1% level. The multiple regression equations for the amount of $SO_4{^{2-}}$ at the stream water quality showed that the amount of $NO_3{^-}$, total amount of ion had statistical significance at the 5% level.

• The KIPS Transactions:PartD
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• v.14D no.5
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• pp.459-470
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• 2007

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS(Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme tailed an ASC(Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC's that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC's is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.11-20
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• 2012

Stream data shows a sequence of values changing continuously over time. Due to the nature of stream data, its trend is continuously changing according to various time intervals. Therefore the prediction of stream data must be carried out simultaneously with respect to multiple intervals, i.e. Continuous Multiple Prediction(CMP). In this paper, we propose a Continuous Integrated Hierarchical Temporal Memory (CIHTM) network for CMP based on the Hierarchical Temporal Memory (HTM) model which is a neocortex leraning algorithm. To develop the CIHTM network, we created three kinds of new modules: Shift Vector Senor, Spatio-Temporal Classifier and Multiple Integrator. And also we developed learning and inferencing algorithm of CIHTM network.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.2
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• pp.168-172
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• 2015

In this paper, a balanced bitrate control in transcoding process based on video complexity measure for multi-view system which simultaneously shows multiple channels or video contents in single screen, is proposed. In order to consider the total quality of multiple video streams, the proposed algorithm reduces the complexity of multiple video stream and video quality differences at the same time by controlling bitrates of each stream by weighting when they are stitched for single screen. For the measure of complexity and quality differences between video streams, two different data: histogram of macroblock type and bitrate for each stream are used. The experimental result indicates that proposed algorithm decreases fluctuation of quality difference between videos in the multi-view system.

• Journal of the Korean Institute of Landscape Architecture International Edition
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• no.2
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• pp.120-129
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• 2004

Urban stream restoration projects can improve water quality, wildlife habitats, urban landscape, outdoor recreation spaces, and urban microclimate. The objectives of this research were to investigate temperature cooling effect of urban streams by using satellite imagery, to evaluate environmental variables related to stream cooling effect, and to estimate the cooling effect of the Cheonggye stream restoration project of Seoul, Korea. Findings of this research can be summarized as follows. First, a method of estimating temperature distribution around urban streams by using satellite imagery was developed. Scatter plots of distance from stream edges and average temperature obtained through multiple buffering were used for the estimation. Second, urban temperature cooling effect of streams was estimated by comparing background temperature and temperature of each buffer zone. Third, environmental factors affecting stream cooling effect were also identified. Fourth, the temperature cooling effect of the restoration project was estimated based on three scenarios. An estimated cooling effect based on the average cooling effect of existing tributaries showed the most significant effect; $2.0^{\circ}C$ lower than the present level at the edge of the renovated stream. It was estimated that the temperature of the same area would be $1.4^{\circ}C$ cooler than the present level if the cooling effect of the Yangjaechun was used as the bench mark But the effect would be $1.2^{\circ}C$ lower than the present level if environmental variables related to the temperature cooling effect of urban streams were used as the bench mark.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.103-110
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• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.1-16
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• 2008

Join queries having heavy cost are necessary to Data Stream Management System in Sensor Network where plural short information is generated. It is reasonable that each join operator has a sliding-window constraint for preventing DISK I/O because the data stream represents the infinite size of data. In addition, the join operator should be able to take multiple inputs for overall results. It is possible for the MJoin operator with sliding-windows to do so. In this paper, we consider the data stream environment where multiple MJoin operators are registered and propose MMJoin which deals with issues of building and processing a globally shared query considering characteristics of the MJoin operator with sliding-windows. First, we propose a solution of building the global shared query execution plan. Second, we solved the problems of updating a window size and routing for a join result. Our study can be utilized as a fundamental research for an optimization technique for multiple continuous joins in the data stream environment.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.3-8
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• 2013

In CDMA-based systems, recently, researches on chip-level equalization have been studied in order to improve receiving performance when supporting high-rate data services. In this paper, we consider a chip-level LMMSE (linear minimum mean-squared error) receiver for D-TxAA (dual stream transmit antenna array) based single stream HSDPA MIMO systems using precoding weights. First, we will derive precoding weights for maximizing the total instantaneous received power. We will also analyze the effects of both transmit delay of precoding weights and mobile velocity on chip-level LMMSE receivers, which is verified through computer simulations in various mobile channel environments.