• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.2
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• pp.38-49
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• 1997

In this paper, w describe partitioning large circuits into multiple chips on the programmable FPCB for rapid prototyping. FPCBs consists of areas for FPGAs for logic and interconnect components, and the routing topology among them are predetermined. In the partition problem for FPCBs, the number of wires ofr routing among chips is fixed, which is an additonal constraints to the conventional partition problem. In order to deal with such aconstraint properly we first define a new partition problem, so called the topologybased partition problem, and then propose a heuristic method. The heuristic method is based on the simulated annealing and clustering technique. The multi-level tree clustering technique is used to obtain faster and better prtition results. In the experimental results for several test circuits, the restrictions for FPCB were all satisfied and the needed execution time was about twice the modified K-way partition method for large circuits.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.679-680
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• 2006

이 논문에서는 가장 많이 알려진 tracking 알고리즘인 Particle-Filter 의 단점을 motion vector 를 기반으로 예측한 sampling 방법과 K-means clustering 을 이용하여 해결하려고 한다. Tracking 에서의 문제는 다중의 유사한 객체들이 merge 후 split 될 때 제대로 추적을 하지 못하고 한 객체만을 추적 한다는 데에 있었다. 그리고 split 되어 객체별로 추적이 가능하더라도 이전에 추적한 객체를 올바로 labeling 하지 못하는 문제가 있다는 것이다. 이 merge-split 문제는 개량된 K-means clustering 을 이용하고, labeling 문제는 motion vector 를 이용한 개량된 sampling 방법으로 개선하였다.

• ETRI Journal
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• v.40 no.6
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• pp.788-793
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• 2018

3D reconstruction of urban architecture, land, and roads is an important part of building a "digital city." Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4624-4644
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• 2019

With the development of films, games and animation industry, analysis and reuse of human motion capture data become more and more important. Human motion segmentation, which divides a long motion sequence into different types of fragments, is a key part of mocap-based techniques. However, most of the segmentation methods only take into account low-level physical information (motion characteristics) or high-level data information (statistical characteristics) of motion data. They cannot use the data information fully. In this paper, we propose an unsupervised framework using both low-level physical information and high-level data information of human motion data to solve the human segmentation problem. First, we introduce the algorithm of CFSFDP and optimize it to carry out initial segmentation and obtain a good result quickly. Second, we use the ACA method to perform optimized segmentation for improving the result of segmentation. The experiments demonstrate that our framework has an excellent performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.123-125
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• 2011

A SATA hard disk has been widely used in recent years and NCQ is one of its crucial features. Despite the development from IDE to SATA disk, there is still much room for improvement for a SATA disk. In addition, until now a hard disk is a black box to us and it is very hard to make research at the level of a disk controller. To enhance the performance of NCQ, we try to do I/O clustering over the requests, which combines multiple sequential requests into a single large one. To evaluate the effect of an I/O clustering mechanism, we created a simple but practical SATA hard disk simulator. Experimental results show that the proposed approach is effective in enhancing the I/O performance of a SATA disk.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.10
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• pp.1826-1835
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• 2007

In this paper, we present a new approach for automatic detection and tracking for multiple targets. We combine a highest probability data association(HPDA) algorithm for target detection with a particle filter for multiple target tracking. The proposed approach evaluates the probabilities of one-to-one assignments of measurement-to-track and the measurement with the highest probability is selected to be target- originated, and the measurement is used for probabilistic weight update of particle filtering. The performance of the proposed algorithm for target tracking in clutter is compared with the existing clustering algorithm and the sequential monte carlo method for probability hypothesis density(SMC PHD) algorithm for multi-target detection and tracking. Computer simulation studies demonstrate that the HPDA algorithm is robust in performing automatic detection and tracking for multiple targets even though the environment is hostile in terms of high clutter density and low target detection probability.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.101-109
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• 2008

In general, non-stationary or chaos time series forecasting is very difficult since there exists a drift and/or nonlinearities in them. To overcome this situation, we suggest a new prediction method based on multiple model TS fuzzy predictors combined with preprocessing of time series data, where, instead of time series data, the differences of them are applied to predictors as input. In preprocessing procedure, the candidates of optimal difference interval are determined by using con-elation analysis and corresponding difference data are generated. And then, for each of them, TS fuzzy predictor is constructed by using k-means clustering algorithm and least squares method. Finally, the best predictor which minimizes the performance index is selected and it works on hereafter for prediction. Computer simulation is performed to show the effectiveness and usefulness of our method.

• Smart Structures and Systems
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• v.15 no.3
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• pp.751-767
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• 2015

A new procedure is proposed for assessing probabilistic condition of structures considering effect of measured data uncertainty. In this procedure, multiple Finite Element (FE) models are identified by using weighting vectors that represent the uncertainty conditions of measured data. The distribution of structural parameters is analysed using a Principal Component Analysis (PCA) in relation to uncertainty conditions, and the identified models are classified into groups according to their similarity by using a K-means method. The condition of a structure is then assessed probabilistically using FE models in the classified groups, each of which represents specific uncertainty condition of measured data. Yeondae bridge, a steel-box girder expressway bridge in Korea, is used as an illustrative example. Probabilistic condition of the bridge is evaluated by the distribution of load rating factors obtained using multiple FE models. The numerical example shows that the proposed method can quantify uncertainty of measured data and subsequently evaluate efficiently the probabilistic condition of bridges.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.144-151
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• 2005

We propose an optimization method to reduce the assembly time of chip mounters. Feeder arrangement and assembly sequence are determined considering the multiple feeder assignment. The problem is divided into two sub-problems: feeder arrangement problem and assembly sequence problem. We present mathematical model for each sub-problem. The clustering algorithm and assignment algorithm are applied to solve the feeder arrangement problem. The assignment algorithm and connection algorithm are applied to solve the assembly sequence problem. Simulation results are then presented to verity the usefulness of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.868-871
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• 2009

We propose an global color model based method for tracking motions of multiple human using a networked multiple-camera system in intelligent space as a human-robot coexistent system. An intelligent space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of intelligent space as well. One of the main goals of intelligent space is to assist humans and to do different services for them. In order to be capable of doing that, intelligent space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly.