• Korean Journal of Environmental Agriculture
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• v.21 no.3
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• pp.165-171
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• 2002

A study was conducted to investigate the seasonal changes in water quality of watershed in the Agricultural Environment Promotion Zone. Samples collected were 12 GW (ground water), 2 IW (irrigation water), 2 SW (stream water) in An-Dong City, 4 GW, 6 IW, 11 SW in Young-Yang Gun, and sampling was conducted separately during dry and rainy season. In the ground water, EC and ionic species, except pH, were higher than those in stream water, and especially $NO_3-N$ concentration exceeded the limitation of drinking water. Concentration of ions decreased as the sampling depth was far from the soil surface. During a rainy season, the concentrations of $NO_3-N$ and K in the stream water were slightly higher than those during season. COD was lower during dry season in Yong-Yang, while the trend was contrasted to An-Dong. These results suggest that ground water was polluted by fertilization and compost while streamwater was polluted by loss of soil and organic during the rainy season. Principal chemical components related with changing water quality were EC, $NO_3^-$, Ca, Mg, Na, $Cl^-$, $Cl^-$, $SO_4^-$ in ground water, whereas $NH_4-N$, K, Mg, $Cl^-$, $SO_4^-$ in stream water.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.6
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• pp.85-95
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• 2015

Recent years, nationwide projects for ecological restoration are implemented with emerging issues on the stream ecosystem. In order to enhance effectiveness of the ecosystem restoration and reduce negative impact, the appraisal of effectiveness through the follow-up monitoring and the adaptive management process are executed in consecutive phase. In this study, planning phase, monitoring and adaptive management in Hakui stream which is part of An Yang stream restoration project is introduced as representative ongoing case of effective adaptive management. The aim of this study is to verify the adaptive management process and suggest direction of effective restoration. Restoration project of Hakui stream resulted in increasing number and diversity of species (vegetation, fish, bird, invertbrates, amphibian and reptilia) according to monitoring from 2004 to 2013, and enhancing natural river landscape by evaluation of river naturalness among 2001(before restoration), 2007 (after), 2015 (recent). However, excessive vegetation expansion or sediment deposition on channel over time caused unexpected results such as terrestrialization or degradation of habitats. Adaptive management action such as removing disturbance species (Humulus japonicus)(2007), coppicing willow (2007), release of march snail (2007), creation of wetland (2014) were implemented based on monitoring results. And then appraisal of management action was discussed.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.717-732
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• 2011

Classification in biomedical applications is an important task that predicts or classifies an outcome based on a given set of input variables such as diagnostic tests or the symptoms of a patient. Traditionally the classification algorithms would have to digest a stationary set of historical data in order to train up a decision-tree model and the learned model could then be used for testing new samples. However, a new breed of classification called stream-based classification can handle continuous data streams, which are ever evolving, unbound, and unstructured, for instance--biosignal live feeds. These emerging algorithms can potentially be used for real-time classification over biosignal data streams like EEG and ECG, etc. This paper presents a pioneer effort that studies the feasibility of classification algorithms for analyzing biosignals in the forms of infinite data streams. First, a performance comparison is made between traditional and stream-based classification. The results show that accuracy declines intermittently for traditional classification due to the requirement of model re-learning as new data arrives. Second, we show by a simulation that biosignal data streams can be processed with a satisfactory level of performance in terms of accuracy, memory requirement, and speed, by using a collection of stream-mining algorithms called Optimized Very Fast Decision Trees. The algorithms can effectively serve as a corner-stone technology for real-time classification in future biomedical applications.

• The Korean Journal of Ecology
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• v.14 no.2
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• pp.195-210
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• 1991

The primary succession of the pebble area in gye-bang chon, an upper stream bank of north han river, was investigated by belt transect method from July to October 1990. The stsges of bare area, herbaceous pioneer, perenial herb, woody plants and pine stand were recognized from stream bank to inland. The change of the coverage in herbaceous plants increased with developing sueccessional sere but decreaser with increment of woody plants. The species sequence cyrves vs. relative coverage were geometric in pioneer stage and graduaiiy changed to lognormal y\type as the development of forest. The species diversity was highest during then woody plants stage, probably it would to be the edge effect. The soil properties were not noticeable difference between stream side and inland side. It seems that the vegetational developement was not enough to affect soil accumulation.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.65-73
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• 2008

The telematics data management deals with queries on stream data coming from moving cars. So the stream DBMS should process the large amount of data stream in real-time. In this article, previous research projects are analyzed in the aspects of query processing. And a hybrid model is introduced where query preprocessor is used to process all types of queries in one singe system. Decreasing cost and rapidly increasing Performance of devices may guarantee the utmost parallelism of the hybrid system. As a result, various types of stream DBMS queries could be processed in a uniform and efficient way in a single system.

• Journal of KIISE:Databases
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• v.36 no.3
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• pp.226-234
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• 2009

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Due to the characteristics of a data stream, it is impossible to save all the data elements of a data stream. Therefore it is necessary to define a new synopsis structure to store the summary information of a data stream. For this purpose, this paper proposes a cuboid prefix tree that can be effectively employed in evaluating an iceberg query over data streams. A cuboid prefix tree only stores those itemsets that consist of grouping attributes used in GROUP BY query. In addition, a cuboid prefix tree can compute multiple iceberg queries simultaneously by sharing their common sub-expressions. A cuboid prefix tree evaluates an iceberg query over an infinitely generated data stream while efficiently reducing memory usage and processing time, which is verified by a series of experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.736-744
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• 2006

For the handhold devices, minimizing repetitive CPU operations such as multiplications is a major factor for their performances. In this paper, we propose efficient algorithms for finding similar sequences from streaming time-series data such as stock prices, network traffic data, and sensor network data. First, we formally define the problem of similar subsequence matching from streaming time-series data, which is called the stream sequence matching in this paper. Second, based on the window construction mechanism adopted by the previous subsequence matching algorithms, we present an efficient window-based approach that minimizes CPU operations required for stream sequence matching. Third, we propose a notion of window MBR and present two stream sequence matching algorithms based on the notion. Fourth, we formally prove correctness of the proposed algorithms. Finally, through a series of analyses and experiments, we show that our algorithms significantly outperform the naive algorithm. We believe that our window-based algorithms are excellent choices for embedded stream sequence matching in handhold devices.

• Convergence Security Journal
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• v.18 no.4
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• pp.27-33
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• 2018

Stream cipher is an one-time-pad type encryption algorithm that encrypt plaintext using simple operation such as XOR with random stream of bits (or characters) as symmetric key and its security depends on the randomness of used stream. Therefore we can design more secure stream cipher algorithm by using mathematical analysis of the stream such as period, linear complexity, non-linearity, correlation-immunity, etc. The key stream in stream cipher is generated in linear feedback shift register(LFSR) having characteristic polynomial. The primitive polynomial is the characteristic polynomial which has the best security property. It is used widely not only in stream cipher but also in SEED, a block cipher using 8-degree primitive polynomial, and in Chor-Rivest(CR) cipher, a public-key cryptosystem using 24-degree primitive polynomial. In this paper we present the concept and various properties of primitive polynomials in Galois field and prove the theorem finding the number of irreducible polynomials and primitive polynomials over $F_p$ when p is larger than 2. This kind of research can be the foundation of finding primitive polynomials of higher security and developing new cipher algorithms using them.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.04a
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• pp.167-174
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• 2004

Several metalliferous and coal mines, including Myungjin, Seojin and Okdong located at the upper watershed of Okdong stream, were abandoned or closed since 1988 due to the mining industry promotion policy and thus disposed an enormous amount of mining wastes without a proper treatment facilities, resulting in water pollution in the downstream areas. AMD and waste effluents from the closed coal mines were very strongly acidic showing pH ranges of 2.7 to 4.5 and had a high level of total dissolved solid (TDS) showing the ranges of 1,030 to 1,947 mg/L. Also heavy metal concentrations in these samples such as Fe, Cu, Cd and anion such as sulfate were very high. These parameters of AMD and effluents were considered to be highly polluted as compared to those in the main stream area of the Okdong river and be major pollutants for water and soil in tile downstream area. Pollution indices of the surface water at the upper stream of Okdong river where AMD of the abandoned coal mines was flowed into main stream were in the ranges of 16.3 to 47.1. On the other hand, those at the mid stream where effluents from tailing dams and coal mines flowed into main stream were in tile ranges of 10.6 to 19.5. However, those at the lower stream were ranged from 10.6 to 14.9 These results indicated that mining wastes such as AMD and effluents from the closed mines were tile major source to water pollution at the Okdong stream areas.

• Journal of Environmental Science International
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• v.26 no.12
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• pp.1321-1331
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• 2017

This study reviewed the applicability of the existing flood discharge calculation method on Jeju Island Han Stream and compared this method with observation results by improving the mediating variables for the Han Stream. The results were as follows. First, when the rain-discharge status of the Han Stream was analyzed using the flood discharge calculation method of the existing design (2012), the result was smaller than the observed flood discharge and the flood hydrograph differed. The result of the flood discharge calculation corrected for the curve number based on the terrain gradient showed an improvement of 1.47 - 6.47% from the existing flood discharge, and flood discharge was improved by 4.39 - 16.67% after applying the new reached time. In addition, the sub-basin was set separately to calculate the flood discharge, which yielded an improvement of 9.92 - 32.96% from the existing method. In particular, the steepness and rainfall-discharge characteristics of Han Stream were considered in the reaching time, and the sub-basin was separated to calculate the flood discharge, which resulted in an error rate of -8.77 to 8.71%, showing a large improvement of 7.31 - 28.79% from the existing method. The flood hydrograph also showed a similar tendency.