• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.255-264
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• 2002

The topography is recognized as an important factor in determining the streamflow response of watershed to precipitation. In watershed analysis, stream networks are very important parameters. Each DEM grid size and flowaccumulation threshold value of drainage accumulation matrix have influence on stream networks extracted by using grid DEM. Therefore, stream networks extracted from DEM varies with each DEM grid size and flowaccumulation threshold value. Generally, small threshold values will generate more detailed stream network with higher drainage density High threshold values will generate coarser stream networks. In this paper, total stream length in the study area was used to calculate the flowaccumulation threshold value by each DEM grid size. Stream network was derived by each DEM grid size, which is applied flowaccumulation threshold value. Regression equation was derived by correlation between flowaccumulation threshold value and each DEM grid size.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.938-958
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• 2024

Unsupervised Video Object Segmentation (UVOS) is a highly challenging problem in computer vision as the annotation of the target object in the testing video is unknown at all. The main difficulty is to effectively handle the complicated and changeable motion state of the target object and the confusion of similar background objects in video sequence. In this paper, we propose a novel deep Dual-stream Co-enhanced Network (DC-Net) for UVOS via bidirectional motion cues refinement and multi-level feature aggregation, which can fully take advantage of motion cues and effectively integrate different level features to produce high-quality segmentation mask. DC-Net is a dual-stream architecture where the two streams are co-enhanced by each other. One is a motion stream with a Motion-cues Refine Module (MRM), which learns from bidirectional optical flow images and produces fine-grained and complete distinctive motion saliency map, and the other is an appearance stream with a Multi-level Feature Aggregation Module (MFAM) and a Context Attention Module (CAM) which are designed to integrate the different level features effectively. Specifically, the motion saliency map obtained by the motion stream is fused with each stage of the decoder in the appearance stream to improve the segmentation, and in turn the segmentation loss in the appearance stream feeds back into the motion stream to enhance the motion refinement. Experimental results on three datasets (Davis2016, VideoSD, SegTrack-v2) demonstrate that DC-Net has achieved comparable results with some state-of-the-art methods.

• Journal of Korean Society on Water Environment
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• v.31 no.5
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• pp.491-506
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• 2015

Distributed models represent watersheds using a network of numerous, uniform calculation units to provide spatially detailed and consistent evaluations across the watershed. However, these models have a disadvantage in general requiring a high computing cost. Semi-distributed models, on the other hand, delineate watersheds using a simplified network of non-uniform calculation units requiring a much lower computing cost than distributed models. Employing a simplified network of non-uniform units, however, semi-distributed models cannot but have limitations in spatially-consistent simulations of hydrogeochemical processes and are often not favoured for such a task as identifying critical source areas within a watershed. Aiming to overcome these shortcomings of both groups of models, a hybrid watershed model STREAM (Spatio-Temporal River-basin Ecohydrology Analysis Model) was developed in this study. Like a distributed model, STREAM divides a watershed into square grid cells of a same size each of which may have a different set of hydrogeochemical parameters reflecting the spatial heterogeneity. Like many semi-distributed models, STREAM groups individual cells of similar hydrogeochemical properties into representative cells for which real computations of the model are carried out. With this hybrid structure, STREAM requires a relatively small computational cost although it still keeps the critical advantage of distributed models.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.273-276
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• 2002

Watershed boundary and stream network can be extracted from DEM(Digital Elevation Model) using GIS software such as ARC/INFO or ArcView Spatial Analyst. However, there exist many errors in the generated watershed boundary and stream network just by operating sink removal function of the present software. This paper present the error reducing method to delineate watershed boundary and generate stream network especially in plane areas by using stream burning techniques known as Fillburn and Agree bum. These preprocessing techniques of DEM dramatically decreased the errors comparing with the results by no-bum DEM.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.2
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• pp.1-12
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• 2008

Home network is a technology that provides possibilities of monitoring/controling/mutilating-recognition between optional home network machines in residences. Currently, home network or other networks like entertainment, residential electronic networks are jumbled together with heterogeneous networks in a rampaging condition. In a reality of high expectation for home networks system like the mutual application for various machines, we are required to have the unification technology for conveniences to satisfy expectations. This thesis reflects how to develop Java applications or mutual products based on convenient interfaces actually that process various sensors which create real time data stream in Java platform through Java based sensor data-stream processing embedded middleware design and realization in real time.

• 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.29 no.3
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• pp.343-353
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• 2013

Flow duration curve (FDC) can be developed by linking the daily flow data of stream flow monitoring network to 8-day interval flow data of the unit watersheds for the management of Total Maximum Daily Loads. This study investigated the applicable method for the development of long term FDC with the selection of the stream flow reference sites, and suggested the development of the FDC in 4 river basins. Out of 142 unit watersheds in 4 river basins, 107 unit watersheds were shown to estimate daily flow data for the unit watersheds from 2006 to 2010. Short term FDC could be developed in 64 unit watersheds (45%) and long term FDC in 43 unit watersheds (30%), while other 35 unit watersheds (25%) were revealed to have difficulties in the development of FDC itself. Limits in the development of the long term FDC includes no stream monitoring sites in certain unit watersheds, short duration of stream flow data set and missing data by abnormal water level measurements on the stream flow monitoring sites. To improve these limits, it is necessary to install new monitoring sites in the required areas, to keep up continuous monitoring and make normal water level observations on the stream flow monitoring sites, and to build up a special management system to enhance data reliability. The development of long term FDC for the unit watersheds can be established appropriately with the normal and durable measurement on the selected reference sites in the stream flow monitoring network.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1141-1153
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• 2010

This paper introduces ONLIS(Overlay Multicast Network for Live IPTV Service), a novel overlay multicast network optimized to deliver live broadcast IPTV stream. We analyzed IPTV reference model of ITU-T IPTV standardization group in terms of network and stream delivery from the source networks to the customer networks. Based on the analysis, we divide IPTV reference model into 3 networks; source network, core network and access network, ION(Infrastructure-based Overlay Multicast Network) is employed for the source and core networks and PON(P2P-based Overlay Multicast Network) is applied to the access networks. ION provides an efficient, reliable and stable stream distribution with very negligible delay while PON provides bandwidth efficient and cost effective streaming with a little tolerable delay. The most important challenge in live P2P streaming is to reduce end-to-end delay without sacrificing stream quality. Actually, there is always a trade-off between delay & stream quality in conventional live P2P streaming system. To solve this problem, we propose two approaches. Firstly, we propose DSPT(Distributed Streaming P2P Tree) which takes advantage of combinational overlay multicasting. In DSPT, a peer doesn't fully rely on SP(Supplying Peer) to get the live stream, but it cooperates with its local ANR(Access Network Relay) to reduce delay and improve stream quality. When RP detects bandwidth drop in SP, it immediately switches the connection from SP to ANR and continues to receive stream without any packet loss. DSPT uses distributed P2P streaming technique to let the peer share the stream to the extent of its available bandwidth. This means, if RP can't receive the whole stream from SP due to lack of SP's uploading bandwidth, then it receives only partial stream from SP and the rest from the ANR. The proposed distributed P2P streaming improves P2P networking efficiency.

• Spatial Information Research
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• v.19 no.1
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• pp.127-133
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• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.255-261
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• 2008

This paper describes a network framework that support network based humanoid. The framework utilizes middleware such as CORBA (ACE/TAO) that provides PnP capability for network based humanoid. The network framework transfers data gathered from a network based humanoid to a processing group that is distributed on a network. The data types are video stream, audio stream and control data. Also, the network framework transfers service data produced by the processing group to the network based humanoid. By using this network framework, the network based humanoid can provide high quality of intelligent services to user.