• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.51-56
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• 2022

In space based constellation network, users are allowed to enter or leave the network arbitrarily. Hence, the number, identities and transmitted data of active users vary with time and have considerable impacts on the receiver's performance. The so-called problem of multiuser detection means identifying the identity of each active user and detecting the data transmitted by each active user. Traditional methods assume that the number of active users is equal to the maximum number of users that the network can hold. The model of traditional methods are simple and the performance are suboptimal. In this paper a Maximum A Posteriori Probability (MAP) based multiuser detection method is proposed. The proposed method models the activity state of users as Markov chain and transforms multiuser detection into searching optimal path in grid map with BCJR algorithm. Simulation results indicate that the proposed method obtains 2.6dB and 1dB E_b/N₀ gains respectively when activity detection error rate and symbol error rate reach 10^-3, comparing with reference methods.

• Journal of the Korean GEO-environmental Society
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• v.15 no.1
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• pp.69-77
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• 2014

The objective of this study is to compare flood inundation models for small stream basin. HEC-RAS model was used for the analysis of one dimensional hydraulics and HEC-GeoRAS, Ras Mapper and RiverCAD models were applied for the flood inundation analysis in Gum Chung stream. Flood inundations are to simulate by flood inundation models using observed data and rainfall on each frequency and to compare with inundation area based on the flood plain maps. The results of this study are as follows; Area of flood inundations by HEC-GeoRAS model is similar to that of flood plain map and appears in order of RAS Mapper and RiverCAD model. Flood inundation area by RiverCAD model is to estimate lager than that of RAS Mapper and HEC-GeoRAS model in flood area on each frequency and the results show that they have a little difference in models of flood inundation analysis at small stream. Comparing the area of flood inundations by flood depth, the results of three models are relatively similar in flood depth as 2.0 m below, and RiverCAD model shows a significant difference in flood depth as 2.0 m or more.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.2
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• pp.63-70
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• 1997

This paper proposes a new algorithm for recognizing polyhedral objects using a single 2-D image. It is base don a new representation scheme having two level hierarchey. In the lower level, geometrical features of each primitive surface are represented using their signatures and the variation of signature due to rotation is represented suing the rotation map. In the higher level, topological features are represented in the inter-surface description table(SDT). Based on the proposed representaton scheme, loer level database searched to find a matching primitive surface. The srotation map determines the degree of rotation as well as the matchness. If all surfaces in a test object find their matching primitive surfaces, its structural information is compared with the SDTs of object models. If primitive surfaces of a test object equal to tha tof certain model and satisfy inter-surfaces relationship in SDT, a test object is recognized as the model.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.1
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• pp.67-84
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• 1995

Five-axis NC machining is advanced machining technology by which highly geometrically complicated parts can be machined accurately with high machinability. In this paper, we investigate the problems of determining the machinability and part setup orientation for a given surface models. We first develop kinematic model of the five-axis machines based on the axis configuration, then develop algorithms for determining the feasibility of machining by one setup(machinability) and the part orientation for the C,A and A,B type configuration. The machinability is determined by computationally efficient procedure for finding the intersection between the feasible area on the sphere and the numerical map called binary spherical map(BSM), and the part setup is chosen such that the rotational range is minimized among the feasible configurations. The developed algorithms are tested by numerical simulations, convincing they can be readily implemented on the CAD/CAM system as an automated process planner giving the efficient machine type and setup for NC machining.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.11a
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• pp.985-987
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• 2011

This paper includes a development of a starting time prediction model for a derivative engine. For this derivative engine design, a new map expansion method, Modified Pump Scaling Law(MPS), has been applied and expand the maps to sub-idle range. From loss characteristics of the reference engine, loss models for the derivative engine have been developed considering different pressure, temperature, and engine configurations. Starting time predictions of the derivative engine shows preferable results comparing test results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2301-2306
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• 2005

Even if there are lots of researches on localization using 2D range finder in static environment, very few researches have been reported for robust real-time localization of mobile robot in uncertain and dynamic environment. In this paper, we present a new localization method based on ICP(Iterative Closest Point) algorithm for navigation of mobile robot under dynamic or uncertain environment. The ICP method is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. We use the method to align global map with 2D scanned data from range finder. The proposed algorithm accelerates the processing time by uniformly sampling the line fitted data from world map of mobile robot. A data filtering method is also used for threshold of occluded data from the range finder sensor. The effectiveness of the proposed method has been demonstrated through computer simulation and experiment in an office environment.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.2
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• pp.71-79
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• 1998

In this paper, we propose a new mART(modified ART) neural network by combining the winner neuron definition method of SOM(self-organizing map) and the real-time adaptive clustering function of ART(adaptive resonance theory) and construct it in a modular structure, for the purpose of organizing the feature maps of three dimensional targets. Being constructed in a modular structure, the proposed modular mART can effectively prevent the clusters from representing multiple classes and can be trained to organze two dimensional distortion invariant feature maps so as to recognize targets with three dimensional distortion. We also present the recognition result and self-organization perfdormance of the proposed modular mART neural network after carried out some experiments with 14 tank and fighter target models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.67-73
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• 2008

In the Markov network which models disparity map with the Markov Random Field(MRF), the belief propagation algorithm is operated by message passing between nodes corresponding to each pixels. Belief propagation algorithm required much iteration for accurate result. In this paper, we propose the stereo matching algorithm using belief propagation in multi-resolution domain. Multi-resolution method based on wavelet or lifting can reduce the search area, therefore this algorithm can generate disparity map with fast speed.

• Speech Sciences
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• v.7 no.1
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• pp.31-37
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• 2000

This paper concerns effective speaker adaptation methods to solve the over-training problem in speaker verification, which frequently occurs when modeling a speaker with sparse training data. While various speaker adaptations have already been applied to speech recognition, these methods have not yet been formally considered in speaker verification. This paper proposes speaker adaptation methods using a combination of MAP and MLLR adaptations, which are successfully used in speech recognition, and applies to speaker verification. Experimental results show that the speaker verification system using a weighted MAP and MLLR adaptation outperforms that of the conventional speaker models without adaptation by a factor of up to 5 times. From these results, we show that the speaker adaptation method achieves significantly better performance even when only small training data is available for speaker verification.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.153.5-153
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• 2001

This paper presents a simple modeling system that constructs 3D models from an indoor cylindrical environment map using all of the available geometry of the interior structure such as vertical and horizontal lines and parallel and perpendicular planes. The indoor scene abstract model is created through this system and the navigation through the process of 3D reconstruction. This system first automatically detects the vanishing points in a cylindrical environment map from parallel lines and planes, and determines the indoor scene topology previously defined using this information. The determined topology enables he user intervention UI simply construct a 3D model by using the photogrammetry. The modeling system can be ...