• Journal of the Korean Society for Marine Environment & Energy
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• v.6 no.1
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• pp.11-20
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• 2003

The pollution loads flowing into Mokpo harbour from land in dry case were estimated on the bases of the seasonal flow rates and the seasonal water qualities of streams and effluents located around Mokpo harbour. Average daily amount of fresh water Stowing into Mokpo harbour obtained by the inflow rate data of 4 seasons was found to be about 5.5×10/sup 6/㎥/day and annual inflow rate to be about 2×10/sup 9/㎥/year. The seasonal flow rates of effluents iron Yongsan lake were above 90％ of total flow rates of all inflows in 4 seasons. The concentrations of COD, TSS, TIN and TP at 9 inflow stations Iron streams and effluents in 4 seasons were shown to be in the ranges of 2.87~42.69㎎/ℓ, 3.65~1080.32㎎/ℓ, 0.083~89.744㎎/ℓ and 0.028~6.926㎎/ℓ, respectively. The average loads of COD, TSS, TIN and TP into Mokpo harbour estimated by the data of 4 seasons were found to be about 37 ton/day, 64 ton/day, 13 ton/day and 1.2 ton/day, respectively. The loads of COD, TSS, TIN and TP into Mokpo harbour in summer were shown to be about 82 ton/day, 159 ton/day, 14 ton/day and 2 ton/day, respectively. The main source of pollution loads into Mokpo harbour was found to be the effluent of Yongsan lake.

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.147-158
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• 2009

Recently, the data model in stream data environment has massive, continuous, and infinity properties. However the stream data processing like query process or data analysis is conducted using a limited capacity of disk or memory. In these environment, the traditional frequent pattern discovery on transaction database can be performed because it is difficult to manage the information continuously whether a continuous stream data is the frequent item or not. In this paper, we propose the method which we are able to predict the frequent items using the regression model on continuous stream data environment. We can use as a prediction model on indefinite items by constructing the regression model on stream data. We will show that the proposed method is able to be efficiently used on stream data environment through a variety of experiments.

• The Journal of the Petrological Society of Korea
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• v.25 no.4
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• pp.361-372
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• 2016

Lahar, one of catastrophic events, has the potential to cause the loss of life and damage to infrastructure over inhabited areas. This study using Laharz_py program, was performed schematic prediction on the impact area of lahar hazards at the Mt. Halla volcano, Jeju island. In order to comprehensively address the impact of lahar for the Mt. Halla, two distinct parameters, H/L ratio and lahar volume, were selected to influence variable for Laharz_py simulation. It was carried out on the basis of numerical simulation by estimating a possible lahar volumes of 30,000, 50,000, 70,000, 100,000, 300,000, $500,000m^3$ according to H/L ratios (0.20, 0.22 and 0.25) was applied. Based on the numerical simulations, the area of the proximal hazard zone boundary is gradually decreased with increasing H/L ratio. The number of streams which affected by lahar tended to decrease with increasing H/L ratio. In the case of H/L ratio 0.20, three streams (Gwangryeong stream, Dogeun stream, Han stream) in the Jeju-si area and six streams (Gungsan stream, Hogeun stream, Seohong stream, Donghong stream, Bomok stream, Yeong stream-Hyodon stream) in the Seogwipo-si area are affected. In the case of H/L ratio 0.22, two streams (Gwangryeong stream and Han stream) in the Jeju-si area and five streams (Gungsan stream, Seohong stream, Donghong stream, Bomok stream, Yeong stream-Hyodon stream) in the Seogwipo-si area are affected. And in the case of H/L ratio 0.25, two streams (Gwangryeong stream and Han stream) in the Jeju-si area and one stream (Yeong stream-Hyodon stream) in the Seogwipo-si area are affected. The results of this study will be used as basic data to create a risk map for the direct damage that can be caused due to volcanic hazards arising from Mt. Halla.

• Korean Journal of Ecology and Environment
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• v.45 no.2
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• pp.158-173
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• 2012

The objectives of this study were to analyze the longitudinal gradient and temporal variations of water quality in Daecheong Reservoir in relation to the major inflowing streams from the watershed, during 2001~2010. For the study, we selected 7 main-stream sites of the reservoir along the main axis of the reservoir, from the headwater to the dam and 8 tributary streams. In-reservoir nutrients of TN and TP showed longitudinal declines from the headwater to the dam, which results in a distinct zonation of the riverine ($R_z$, M1~M3), transition ($T_z$, M4~M6), and lacustrine zone ($L_z$, M7) in water quality, as shown in other foreign reservoirs. Chlorophyll-a (CHL) and BOD as an indicator of organic matter, were maximum in the $T_z$. Concentration of total phosphorus (TP) was the highest (8.52 $mg\;L^{-1}$) on March in the $R_z$, and was the highest (165 ${\mu}g\;L^{-1}$) in the $L_z$ on July. Values of TN was the maximum (377 ${\mu}g\;L^{-1}$) on August in the $R_z$, and was the highest (3.76 $mg\;L^{-1}$) in the $L_z$ on August. Ionic dilution was evident during September~October, after the monsoon rain. The mean ratios of TN : TP, as an indicator of limiting factor, were 88, which indicates that nitrogen is a surplus for phytoplankton growth in this system. Nutrient analysis of inflowing streams showed that major nutrient sources were headwater streams of T1~T2 and Ockcheon-Stream of T5, and the most influential inflowing stream to the reservoir was T5, which is located in the mid-reservoir, and is directly influenced by the waste-water treatment plants. The key parameters, influenced by the monsoon rain, were TP and suspended solids (SS). Empirical models of trophic variables indicated that variations of CHL in the $R_z$ ($R^2$=0.044, p=0.264) and $T_z$ ($R^2$=0.126, p=0.054) were not accounted by TN, but were significant (p=0.032) in the $L_z$. The variation of the log-transformed $I_r$-CHL was not accounted ($R^2$=0.258, p=0.110) by $I_w$-TN of inflowing streams, but was determined ($R^2$=0.567, p=0.005) by $I_w$-TP of inflowing streams. In other words, TP inputs from the inflowing streams were the major determinants on the in-reservoir phytoplankton growth. Regression analysis of TN : TP suggested that the ratio was determined by P, rather than N. Overall, our data suggest that TP and suspended solids, during the summer flood period, should be reduced from the eutrophication control and P-input from Ockcheon-Stream should be controlled for water quality improvement.

• Journal of Advanced Navigation Technology
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• v.6 no.4
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• pp.290-295
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• 2002

In Mpeg-4 system, objects are composed of ES(Elementary Stream). Each of the objects is managed independently by object-based coding and is transmitted via DMIF(Delivery Multimedia Integration Framework). The data streams in Mpeg-4 are transmitted with using DVB-Data Carousel which can improve the reliability and efficiency by cyclic retransmission. This paper describes a system which transmits some part of data stream of Mpeg-4 object with using DVB-Data Carousel to clients via satellite. This also uses a performance enhancing proxy server for reducing round trip time between ground network and satellite.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.6-14
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• 2020

On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.

• Spatial Information Research
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• v.16 no.2
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• pp.219-236
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• 2008

Data stream collected from sensors contain a large amount of useful information including causality relationships. The causality join query for data stream is to retrieve a set of pairs (cause, effect) from streams of data. A part of causality pairs may however be lost from the query result, due to the delay from sensors to a data stream management system, and the limited size of sliding windows. In this paper, we first investigate spatial, temporal, and spatio-temporal aspects of the causality join query for data stream. Second, we propose several strategies for sliding window management based on these observations. The accuracy of the proposed strategies is studied by intensive experiments, and the result shows that we improve the accuracy of causality join query in data stream from simple FIFO strategy.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.655-664
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• 2001

The continuous data such as video streams and voice analog signals can be modeled as multidimensional data sequences(MDS's) in the feature space, In this paper, we investigate the clustering technique for multidimensional data sequence, Each sequence is represented by a small number by hyper rectangular clusters for subsequent storage and similarity search processing. We present a linear clustering algorithm that guarantees a predefined level of clustering quality and show its effectiveness via experiments on various video data sets.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.11-22
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• 2019

The objective of this study was to improve the cross-sectional area and height estimation method using stream width. Stream water levels should be calculated together to simulate inundation of agricultural land. However, cross-sectional survey data of small rural rivers are insufficient. The previous study has developed regression equations between the width and the cross-sectional area and between the width and the height of stream cross-section, but can not be applied to a wide range of stream widths. In this study, cross-sectional survey data of 6 streams (Doowol, Chungmi, Jiseok, Gam, Wonpyeong, and Bokha stream) were collected and divided into upstream, midstream and downstream considering the locations of cross-sections. The regression equations were estimated using the complete data. $R^2$ between the stream width and cross-sectional area was 0.96, and $R^2$ between width and height was 0.81. The regression equations were also estimated using divided data for upstream, midstream and downstream considering the locations of cross-sections. The range of $R^2$ between the stream width and cross-sectional area was 0.86 - 0.91, and the range of $R^2$ between width and height was 0.79 ? 0.92. As a result of estimating the cross-sections of 6 rivers using the regression equations, the regression equations considering the locations of cross-sections showed better performance both in the cross-sectional area and height estimation than the regression equations estimated using the complete data. Hydrologic Engineering Center - River Analysis System (HEC-RAS) was used to simulate the flood stage analysis of the estimated and the measured cross-sections for 50-year, 100-year, and 200-year frequency floods. As a result of flood stage analysis, the regression equations considering the locations of cross-sections also showed better performance than the regression equations estimated using the complete data. Future research would be needed to consider the factors affecting the cross-sectional shape such as river slope and average flow velocity. This study can be useful for inundation simulation of agricultural land adjacent to an unmeasured stream.