• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.91-96
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• 2009

In this paper, interoperability in heterogeneous wireless mesh network, and mesh nodes for providing efficient IP mobility technique offers multi-hop ARP. Heterogeneous wireless mesh networks to MANETs based on a wireless mesh network backbone and non-MANET architecture is based on a client wireless mesh network and the two mobile networks, combined with a hybrid wireless mesh network are separate. In two different hybrid wireless mesh network routing protocols used to connect the two protocols in the protocol conversion at the gateway to parallel processing problems seriously overload occurs. All of the network reliability and stability are factors that reduce. Therefore, for efficient integration with L3 routing protocols, design techniques to build ARP multi-hop go through the experiment to increase the number of mesh nodes, the packet forwarding rate and an increased hop number of the node was to ensure reliability and stability.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.430-436
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• 2014

Matrix-star and Half-Pancake graphs are modified versions of Star graphs, and has some good characteristics such as node symmetry and fault tolerance. This paper analyzes embedding between Matrix-star and Half-Pancake graphs. As a result, Matrix-star graphs $MS_{2,n}$ can be embedded into Half-Pancake graphs $HP_{2n}$ with dilation 5 and expansion 1. Also, Half Pancake Graphs, $HP_{2n}$ can be embedded into Matrix Star Graphs, $MS_{2,n}$ with the expansion cost, O(n). This result shows that algorithms developed from Star Graphs can be applied at Half Pancake Graphs with additional constant cost because Star Graphs, $S_n$ is a part graph of Matrix Star Graphs, $MS_{2,n}$.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.6
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• pp.899-905
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• 2013

In this paper, we focus on how to calibrate multi-cameras easily and how to efficiently detect quad-copters with small-numbered particles. Each particle is a six dimensional vector that is composed of 3D position and 3D orientation of a quad-copter in the space. Due to curse of dimensionality, that leads to explosive computational costs with a large amount of high-dimensioned particles. To detect efficiently, we need to put more particles in very promising spaces and few particles in other spaces. Though computational cost is lowered by minimizing particles, in order to track a quad-copter with multiple cameras in real-time, multiple images from the cameras should be synchronized and analyzed. Therefore, lots of the computations still need to be done. Because of this, GPGPU(General-Purpose computing on Graphics Processing Units) is implemented for parallel computing. This method has been successfully tested and gives accurate results in practical situations.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.697-708
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• 2003

In a software product line approach, developers first develop common software architecture and components by analyzing the characteristics of all software members, and then produce each application by integrating components. The approach is considered very effective means for developing and maintaining in parallel a software product family. Main disadvantage of this approach is that it requires a big up-front investment in preparing product line. Therefore, it takes time to deliver the first version. In this paper, we present an incremental method to develop software families, which requires small additional cost for initial versions and allows an organization to move smoothly to full-scale product line. We present our method by explaining how to record and upgrade the results of variations analysis, and show the application of our method by developing a family of YBS. Our method is a low-risk approach that can be effectively applied to an organization that starts developing software systems but has to deliver the first versions quickly to the market.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12B
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• pp.758-766
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• 2007

IStreaming services with a client-server architecture have scalability problem because a server cannot accomodate clients more than its processing capability. This paper introduces a case study for implementing H.264 streaming system based on P2P architecture in order to provide scalable and stable broadcast streaming services over the internet. The prototype system called OmniCast264 consists of the H.264 encoding server, the streaming server, the proxy server, and peer nodes. The proxy server dynamically manages placement of the peer nodes on the P2P network. Omnicast264 has the concepts of distributed streaming loads, real-time playback, error-robustness and modularity. Thus, it can provide large-scale broadcast streaming services. Finally, we have built P2P streaming systems with 12 PCs connected serially or in parallel. The experiment shows that OmniCast264 can provide real-time playback.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.110-115
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• 2010

Recently the deeply underground tunnels have been increased along the subway railroads of urban area compared to the past subway railroads. The Shin-Gum-Ho subway station (the Fifth lines, the depth : 46m) which is the third among the deep subway stations in the Korea was chosen as the model of deeply underground stations, and attempted to do simulation of fire. This station consists of three entrance, the basement first floor (B1), the basement second floor (B2), the basement eighth floor or platform (B8) and escalators and stairs from B2 to B8. The total number of grid was about 9,000,000 to make simulation of fire and smoke from the platform to entrance in this research, and the grid system was divided into 19 blocks to increase the efficiency of this simulation. The FDS (Fire Dynamics Simulation) was chosen to make the simulation of fire, and the model of turbulent flow was LES (Large Eddy Simulation). Each block is processed in a CPU using parallel processing of MPI (Message Passing Interface). The resource of CPU for this simulation is a ten of Intel 3.0 GHz Dual CPU (20 CPU).

• The KIPS Transactions:PartD
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• v.13D no.2 s.105
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• pp.223-234
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• 2006

Branching and merging have been being the outstanding methods for SCM in terms of supporting parallel developments. Since well-known commercial merging tools based on textual merging have not detecting semantics conflicts, they can cause semantic errors in the result of merging. Although a lot of researches for detecting semantic conflict and merging up to recently, these researches have been doing individually. Therefore, it is necessary for a research detecting semantic conflict on textual merging and solving it. In this paper, we propose a new method for merging which preserve semantics on textual merging. The method merging two revisions from a source program is as follows : 1) defining changing operations, which include Update, Delete, and Insert operation, per line on two revisions corresponding to the line in source program, 2) detecting textual conflicts and semantic conflict in terms of executional behaviors, 3) solving these conflicts before merging. So, the proposed method can be regarded as a hybrid method that combines a method of textual merging and a behavioral semantic merging.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.141-148
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• 2017

The current advancement of mobile devices enables users to collect a sequence of user positions by use of the positioning technology and thus the related research regarding positioning or location information are quite arising. An individual mobility model based on positioning data and time data are already established while group mobility model is not done yet. In this research, group mobility model, an extension of individual mobility model, and the process of establishment of group mobility model will be studied. Based on the previous research of group mobility model from two individual mobility model, a group mobility model with more than two individual model has been established and the transition pattern of the model is represented by Markov chain. In consideration of real application, the computing time to establish group mobility mode from huge positioning data has been drastically improved by use of GPGPU comparing to the use of traditional multicore systems.

• Journal of IKEEE
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• v.24 no.1
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• pp.225-231
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• 2020

In this paper, we propose a method to accelerate BWN based on FPGA with limited resources for embedded system. Because of the limited number of logic elements available, a single computing unit capable of handling Conv-layer, FC-layer of various sizes must be designed and reused. Also, if the input feature map can not be parallel processed at one time, the output must be calculated by reading the inputs several times. Since the number of available BRAM modules is limited, the number of data bits in the BWN accelerator must be minimized. The image classification processing time of the BWN accelerator is superior when compared with a embedded CPU and is faster than a desktop PC and 50% slower than a GPU system. Since the BWN accelerator uses a slow clock of 50MHz, it can be seen that the BWN accelerator is advantageous in performance versus power.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.