• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1156-1173
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• 2021

In this paper, we propose a new joint precoder and postcoder design strategy to support multiple streams per user in multiuser multiple-input multiple-output (MIMO) systems. We propose two step precoding strategies using equal channel gain decomposition and block diagonalization at the transmitter. With the proposed precoder, the multiuser MIMO channel can be decomposed into multiple parallel channels with equal channel gain per user. After applying receive postcoder which is generated and sent by the transmitter, we can use ML based decoder per stream to achieve full receive diversity. Achievable sum rate bound and diversity performance of the proposed algorithm are presented with feedback signaling design and quantitative complexity analysis. Simulation results show that the proposed algorithm asymptotically approaches to the sum rate capacity of the MIMO broadcast channel while maintaining full diversity order.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1367-1383
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• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.275-284
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• 2010

The current multihome-aware protocols (like stream control transmission protocol (SCTP) or parallel TCP for concurrent multipath data transfer (CMT) are not designed for high-capacity and large-latency networks; they often have performance problems transferring large data files over shared long-distance wide area networks. It has been shown that SCTP-CMT is more sensitive to receive buffer (rbuf) constraints, and this rbuf-blocking problem causes considerable throughput loss when multiple paths are used simultaneously. In this research paper, we demonstrate the weakness of SCTP-CMT rbuf constraints, and we then identify that rbuf-blocking problem in SCTP multihoming is mostly due to its loss-based nature for detecting network congestion. We present a simulation-based performance comparison of FAST TCP versus SCTP in high-speed networks for solving a number of throughput issues. This work proposes an end-to-end transport layer protocol (i.e., FAST TCP multihoming as a reliable, delaybased, multihome-aware, and selective ACK-based transport protocol), which can transfer data between a multihomed source and destination hosts through multiple paths simultaneously. Through extensive ns-2 simulations, we show that FAST TCP multihoming achieves the desired goals under a variety of network conditions. The experimental results and survey presented in this research also provide an insight on design decisions for the future high-speed multihomed transport layer protocols.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1554-1559
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• 2000

On ATM networks, MPEG video stream is transferred using CBR or VBR services. But because the MPEG video traffic varies greatly from time to time, it is very difficult to transfer the MPEG steam efficiently without loss of transmission bandwidth. Until now, the study on the traffic analysis and control on a single MPEG video stream has been done by many researchers, but the traffic analysis and control on a multiplexed traffic of multiple MPEG video streams has not been studied by any researcher. This paper proposes a multiplexing method to reduce the PCR and traffic variance of a multiplexed traffic of multiple MPEG video streams. By reducing the PCR of the multiplexed traffic, the multiplexed VBR traffic can be transferred efficiently with less loss of transmission bandwidth.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1385-1402
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• 2019

Quickly picking up some valuable information from massive manufacturing event stream usually faces with the problem of long detection time, high memory consumption and low detection efficiency due to its stream characteristics of large volume, high velocity, many variety and small value. Aiming to solve the problem above for the current complex event processing methods because of not sharing detection during the detecting process for massive manufacturing event streams, an efficient complex event processing method based on multipattern sharing is presented in this paper. The achievement of this paper lies that a multipattern sharing technology is successfully used to realize the quick detection of complex event for massive manufacturing event streams. Specially, in our scheme, we firstly use pattern sharing technology to merge all the same prefix, suffix, or subpattern that existed in single pattern complex event detection models into a multiple pattern complex event detection model, then we use the new detection model to realize the quick detection for complex events from massive manufacturing event streams, as a result, our scheme can effectively solve the problems above by reducing lots of redundant building, storing, searching and calculating operations with pattern sharing technology. At the end of this paper, we use some simulation experiments to prove that our proposed multiple pattern processing scheme outperforms some general processing methods in current as a whole.

• The Journal of Society for e-Business Studies
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• v.18 no.3
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• pp.159-175
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• 2013

Recently, as real-time availability of e-commerce data becomes possible, the requirement of real-time analysis of e-commerce increases significantly. In the real-time analysis of e-commerce data, it is very important to efficiently process continuous join queries between an e-commerce data stream and disk-based large relations. In this paper, we propose an efficient method for processing a continuous join query between an e-commerce data stream and multiple disk-based relations. The proposed method improves the service rate significantly, while reducing the amount of required memory substantially. Through analysis and various experiments, we show the efficiency of the proposed method compared with the previous one in terms of service rate and memory usage.

• Journal of KIISE
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• v.43 no.5
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• pp.606-612
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• 2016

The multi-view video service based on the DASH(Dynamic Adaptive Streaming over HTTP) switches the viewpoint or object which is selected by the user among the multiple video streams captured by multiple cameras. However, the problem is that the conventional DASH-based multi-view video service takes a long time to switch the viewpoint. The reason is that the conventional scheme switches to the new video stream after consuming all buffered segments of the previous video stream. In this paper, we propose a video streaming scheme for minimizing the viewpoint switching delay in the DASH-based multi-view video service. In order to minimize the viewpoint switching delay, the proposed scheme configures the video streams by controlling the GoP (Group of Pictures) size and controls the client buffer based on bandwidth estimation and playback buffer occupancy. Through the experimental results, we prove that the proposed scheme reduces the viewpoint switching delay.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.4
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• pp.150-157
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• 2008

This paper presents a design and implementation of realtime video player that operates on a tiled-display system consisting of multiple PCs to provide a very large and high resolution display. In the proposed system, the master process transmits a compressed video stream to multiple PCs using UDP multicast. All slaves(PC) receive the same video stream, decompress, clip their designated areas from the decompressed video frame, and display it to their displays while being synchronized with each other. A simple synchronization mechanism based on the H/W clock of each slave is proposed to avoid the skew between the tiles of the display, and a flow-control mechanism based on the bit-rate of the video stream and a pre-buffering scheme are proposed to prevent the jitter The proposed system is implemented with Microsoft DirectX filter technology in order to decouple the video/audio codec from the player.

• Journal of Ecology and Environment
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• v.38 no.3
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• pp.307-318
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• 2015

The objectives of this study were to identify multi-level stressors from blood biomarkers to community-level bioindicators and diagnose the stream ecosystem health in polluted streams. Blood chemistry such as total protein ($T_{Pro}$), blood urea nitrogen ($B_{UN}$), total cholesterol ($T_{Cho}$) and $A_{lb}$umin ($A_{lb}$) were analyzed from sentinel fish tissues; the functions of kidney, gill and liver were significantly decreased in the impacted zone ($I_z$), compared to the control zone ($C_z$). Histopathological analysis showed that fish liver tissues were normal in the $C_z$. Fish liver tissues in the $I_z$, however, showed large cell necrosis and degeneration and also had moderate lobular inflammation and inflammatory cell infiltration of lymphocytic histocytes. Species biotic index (SBI) at species level and stream health assessment (SHA) at community level indicated that chemical impacts were evident in the $I_z$ (ecological health; poor - very poor), and this was matched with the blood tissue analysis and histopathological analysis. The impairments of the streams were supported by water chemistry analysis (nitrogen, phosphorus). Tolerance guild analysis and trophic guild analysis of fish were showed significant differences (P < 0.01) between $C_z$ and $I_z$. Overall, multiple parameter analysis from biomarker level (blood tissues) to bioindicator level (community health) showed significantly greater impacts in the $I_z$ than $C_z$. This approach may be effective as a monitoring tool in identifying the multilateral and forthcoming problems related to chemical pollution and habitat degradation of stream ecosystems.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.483-492
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• 2007

Time series of conventional prediction techniques uses the model which is generated from the training step. This model is applied to new input data without any change. If this model is applied directly to stream data, the rate of prediction accuracy will be decreased. This paper proposes an stream data prediction technique using sliding window and regression. This technique considers the characteristic of time series which may be changed over time. It is composed of two steps. The first step executes a fractional process for applying input data to the regression model. The second step updates the model by using its information as new data. Additionally, the model is maintained by only recent data in a queue. This approach has the following two advantages. It maintains the minimum information of the model by using a matrix, so space complexity is reduced. Moreover, it prevents the increment of error rate by updating the model over time. Accuracy rate of the proposed method is measured by RME(Relative Mean Error) and RMSE(Root Mean Square Error). The results of stream data prediction experiment are performed by the proposed technique IMQR(Incremental Multiple Quadratic Regression) is more efficient than those of MLR(Multiple Linear Regression) and SVR(Support Vector Regression).