• Journal of Korea Multimedia Society
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• v.18 no.7
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• pp.793-805
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• 2015

Nowadays the amount of data obtained from advanced weather radars is growing to provide higher spatio-temporal resolution. Accordingly radar data compression is important to use limited network bandwidth and storage effectively. In this paper, we proposed a hierarchical compression method for weather radar data having high spatio-temporal resolution. The method is applied to radar reflectivity and evaluated in aspects of accuracy of quantitative rainfall intensity. The technique provides three compression levels from only 1 compressed stream for three radar user groups-signal processor, quality controller, weather analyst. Experimental results show that the method has maximum 13% and minimum 33% of compression rates, and outperforms 25% higher than general compression technique such as gzip.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.549-557
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• 2012

Spatial phenomena such as environment pollution, disease and the risk of spreading information need a rapid initial response to perceive spread event. Moving data perceive spread event through real-time processing and analysis. To process and analysis the event, spatial-temporal complex event processing is used. Previous spatialtemporal complex event processing is possible basis spatial operator but insufficient apply to design spatialtemporal complex event processing to perceive spatial phenomena of high complexity. This study proposed hierarchical spatio-temporal CEP design which will efficiently manage the fast growing incoming sensor data. The implementation of the proposed design is evaluated with GPS location data of moving vehicles which are used as the incoming data stream for identifying spatial events. The spatial component of existing CEP software engine has been extended during the implementation phase to broaden the capabilities of processing spatio-temporal events.

• Journal of Environmental Science International
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• v.28 no.3
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• pp.303-320
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• 2019

Water quality is characterized by various complex factors. Therefore, a systematic understanding of water quality trends is required to carry out a proper evaluation. In this study, we analyzed the spatio-temporal water quality characteristics of the Nakdong River using five-year data from 2012 to 2016. Data was collected on the pH, DO, BOD, COD, SS, TN, TP, TOC, WT, EC, $NH_3-N$, $NO_3-N$, $PO_4-P$, Chl-a, rainfall, and total and fecal coliforms. A total of 38 water quality measurement stations, from Andong1 to Gupo, were considered. Statistical analyses including trend, cluster, and factor analyses were conducted to identify the dominant water quality components affecting the Nakdong River. The Nakdong River was spatially classified into three groups for up-stream (Andong1 to Sangju1), mid/up-stream (Donam to Dalseong), and mid/down-stream (Hwawonnaru to Gupo) data collection, and temporally into two groups for summer/fall (7~10), and the rest of the season (11~6) data. The water quality of the entire Nakdong River showed trends similar to the mid/down-stream section, which indicates the importance of water quality management in this section. Suspended solids, phosphorus, and coliform groups were established as important factors to be considered in the summer/fall season across the river, especially in the mid/down-stream section. Nitrogen and organic matter were identified as important factors to be considered in the rest of the season, especially in the mid/up-stream section. This study could help determine the water quality components that should be intensively monitored in the Nakdong River.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.89-100
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• 2021

The conservation of stream habitats has been gaining more public attention and fish habitat suitability index (HSI) is an important measure for ecological stream habitat assessment. The fish habitat preference is affected not only by physical stream conditions but also by water quality of which HSI was not available due to the lack of field data. The purpose of this study is to estimate the HSI of Zacco platypus for water quality parameters of water temperature, dissolved oxygen (DO), and biochemical oxygen demand (BOD) using the water environment monitoring data provided by the Ministry of Environment (ME). Fish population data merged with water quality were constructed by spatio-temporal matching of nationwide water quality monitoring data with bio-monitoring data of the ME. Two types of the HSI were calculated by the Instream Flow and Aquatic Systems Group (IFASG) method and probability distribution (Weibull) fitting for the four major river basins. Both the HSIs by the IFASG and Weibull fitting appeared to represent the overall distribution and magnitude of fish population and this can be used in stream fish habitat evaluation considering water quality.

• Journal of Korean Society on Water Environment
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• v.31 no.5
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• pp.507-522
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• 2015

In this study, some of the model verification results of STREAM (Spatio-Temporal River-basin Ecohydrology Analysis Model), a newly-developed hybrid watershed model, are presented for the runoff processes of nonpoint source pollution. For verification study of STREAM, the model was applied to a test watershed and a sensitivity analysis was also carried out for selected parameters. STREAM was applied to the Mankyung River Watershed to review the applicability of the model in the course of model calibration and validation against the stream flow discharge, suspended sediment discharge and some water quality items (TOC, TN, TP) measured at the watershed outlet. The model setup, simulation and data I/O modules worked as designed and both of the calibration and validation results showed good agreement between the simulated and the measured data sets: NSE over 0.7 and $R^2$ greater than 0.8. The simulation results also include the spatial distribution of runoff processes and watershed mass balance at the watershed scale. Additionally, the irrigation process of the model was examined in detail at reservoirs and paddy fields.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.35-44
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• 2009

The emerging notion of data stream has brought many new challenges to the research communities as a consequence of its conceptual difference with conventional concepts of just data. One typical example is data stream processing in sensor networks. The range of data processing considerations in a sensor network is very wide, from physical resource restrictions such as bandwidth, energy, and memory to the peculiarities of query processing including continuous and specific types of queries. In this paper, as one of the physical constraints in data stream processing, we consider the problem of limited memory and propose a new scheme for data stream reduction based on the Principal Component Analysis (PCA) technique. PCA can transform a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. We adapt PCA for the data stream of a sensor network assuming the cooperation of a query engine (or application) with a network base station. Our method exploits the spatio-temporal correlation among multiple measurements from different sensors. Finally, we present a new framework for data processing and describe a number of experiments under this framework. We compare our scheme with the wavelet transform and observe the effect of time stamps on the compression ratio. We report on some of the results.

• Journal of Korean Society on Water Environment
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• v.28 no.4
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• pp.538-550
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• 2012

This study suggests a general methodology which is designed for assessing RDOC behavior at the catchment scale by coupling properly a series of steam flow and water quality simulation models and actual monitoring data set. The modified TANK model in which a river routing function is incorporated to the conventional one is applied to simulate the long-term daily stream flow data, and the simulated stream flow data is combined with the 7-parameter log-linear model coupled to the minimum variance unbiased estimator to simulate the long-term daily water quality (BOD, COD and TOC) loads. Finally, the regression analysis between the usually monitored water quality data (BOD, COD and TOC) and RDOC is combined with the simulated water quality data to manifest the spatio-temporal variability of RDOC flux behavior at the Korean TMDL catchment scale.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.1
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• pp.54-60
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• 2007

The Digital Multimedia Broadcasting(DMB) system is developed to offer high quality multimedia content to the mobile environment. The system adopts the MPEG-4 standard for the main video, audio and other media format. For providing interactive contents, it also adopts the MPEG-4 scene description that refers to the spatio-temporal specifications and behaviors of individual objects. With more interactive contents, the scene description also needs higher bitrate. However, the bandwidth for allocating meta data, such as scene description is restrictive in the mobile environment. On one hand, the DMB terminal renders each media stream according to the scene description. Thus the binary format for scene(BIFS) stream corresponding to the scene description should be decoded and parsed in advance when presenting media data. With this reasoning, the transmission delay of the BIFS stream would cause the delay in transmitting whole audio-visual scene presentations, although the audio or video streams are encoded in very low bitrate. This paper presents the effective optimization technique in adapting the BIFS stream into the expected bitrate without any waste in bandwidth and avoiding transmission delays inthe initial scene description for interactive DMB content.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.105-109
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• 2002

The main ideas of hybrid video coding methods are to reduce the spatial and temporal redundancy for efficient data compression. If compressed video stream is transmitted through the error-prone channel, bitstream can be critically damaged and the spatio-temporal error propagates through successive frames at the decoder because of drift noise in the references between encoder and decoder. In this paper, I propose the lagrangian multiplier selection method in the error-prone environment. Finally, it is shown that the performance comparisons of the R-D optimized mode decision are made against the conventional method and simulation results are given in the following.