• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.120-126
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• 1995

The diffusion neural network can be cfficiently applied to the Gaussian processing. For example, a difference of two Gaussians(DOG) is performed by this network with ease. In this paper, we model a neural network to perform the function /t(.del.${\Delta}^{2}$G) by using the diffusion neural network. This model is used to detect the edges of moving target in image. By this model not only moving target is separated from stationary background but also their trajectories are obtained using accumulated past information in the diffusion neural network. Furthermore this model needs a small number of connections per cell and the connection weights are fixed-valued. Therefore its hardware can be easily implemented with simple structure.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.233-237
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• 2006

This study proposes an innovative measure for evaluating the performance of text clustering. In using K-means algorithm and Kohonen Networks for text clustering, the number clusters is fixed initially by configuring it as their parameter, while in using single pass algorithm for text clustering, the number of clusters is not predictable. Using labeled documents, the result of text clustering using K-means algorithm or Kohonen Network is able to be evaluated by setting the number of clusters as the number of the given target categories, mapping each cluster to a target category, and using the evaluation measures of text. But in using single pass algorithm, if the number of clusters is different from the number of target categories, such measures are useless for evaluating the result of text clustering. This study proposes an evaluation measure of text clustering based on intra-cluster similarity and inter-cluster similarity, what is called CI (Clustering Index) in this article.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.363-363
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• 2000

The conventional algorithms which identify and follow a moving target using a camera located at a fixed position are not appropriate for applying to the cases o( using mobile robots, due to their long processing time. This paper proposes a new tracking algorithm based on the sensing system which uses a line light with a single camera. The algorithm categirizes the motion patterns of a pair of mobile objects into parallel, branching, and merging motion, to decide of which objects the trajectories should be calculated to follow the reference object. Kalman Filter is used to estimate the trajectories of selected objects. The proposed algorithm has shown in the experiments that the mobile robot does not miss the target in most cases.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.35D no.3
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• pp.82-90
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• 1998

A hit-miss transform(HMT) using synthetic structuring elements(SE's) for optical recognition of a moving target is proposed. A moving target which was obtained from a fixed view point has objects. In proposed HMT, SE's are synthesized by using SDF(synthetic discriminant function) algorithm for efficient recognitionof various shapes of true class objects in noisy and cluttered scene. The synthetic hit SE and the synthetic miss SE are composed of SDF of hit SE's and miss SE's for each true class object. Simulation results show the proposed method can be used for the recognition of various shapes of the true class with one one HMT operation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.1-7
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• 2001

For a parametric uncertain system, there are many results on stability analysis, but only a few synthesis methods. In this paper, we proposed a new target polynomial decision method for the parametric uncertain system to stabilize the closed loop system with maximal parametric $l_2$ stability margin. To this, we used both Lipatov Theorem and coefficient diagram method(CDM). To show the effectiveness of the proposed method, we designed a robust controller for the inverted pendulum system with parametric uncertainties using fixed order pole assignment(FOPA) method and its performance was compared with that of the ${\mu}$ synthesis methods.

• Ocean Systems Engineering
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• v.13 no.1
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• pp.1-20
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• 2023

An iterative focused wave generation method is developed and implemented in a local analytic based Navier-Stokes solver. This wave generation method is designed to reproduce the target focused wave by matching the target amplitude spectrum and phase angle. A 4-waves decomposition scheme is utilized to obtain the linearised component of the output wave. A model test studying the interaction between different focused waves and a fixed cylinder is selected as the target for the wave generation approach. The numerical wave elevations and dynamic pressure on the cylinder are compared with the experimental measurement and other state-of-the-art numerical methods' results. The overall results prove that the iterative adjustment method is able to optimize the focused wave generated by a CFD approach.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.173-181
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• 2007

In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5249-5267
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• 2016

Cognitive radio is an efficient technique to improve spectrum efficiency and relieve the pressure of spectrum resources. In this paper, we investigate the spectrum sensing period in cooperative relay cognitive radio networks; analyze the relationship between the available capacity and the signal-to-noise ratio of the received signal of second users, the target probability of detection and the active probability of primary users. Finally, we derive the closed form expression of the optimal spectrum sensing period in terms of maximum throughput. We simulate the probability of false alarm and available capacity of cognitive radio networks and compare optimal spectrum sensing period scheme with fixed sensing period one in these performance. Simulation results show that the optimal sensing period makes the cognitive networks achieve the higher throughput and better spectrum sensing performance than the fixed sensing period does. Cooperative relay cognitive radio networks with optimal spectrum sensing period can achieve the high capacity and steady probability of false alarm in different target probability of detection. It provides a valuable reference for choosing the optimal spectrum sensing period in cooperative relay cognitive radio networks.

• Journal of IKEEE
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• v.25 no.4
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• pp.584-590
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• 2021

This paper proposes a removal method of signal interference between ultrasound sensors where ghost signals due to interference are excluded and correct signal is recognized in distance mensurement using ultrasound sensors. The proposed method detects and excludes ghost signals when previous measured distance is compared to current measured distance and the distance difference exceeds a threshold. The threshold is fixed in conventional methods, so ghost signals cannot be correctly excluded when ultrasound sensor or target object move rapidly. On the contrary, to improve accuracy, the threshold is not fixed in the proposed method, and the threshold is adpatively determined based on the relative velocity when ultrasound sensor or target object move. Experiments of distance measurement with ultrasound signal interference are carried out where multiple ultrasound sensors of same type are exploited with maximum interference, and the results show that the proposed method efficiently exclude ghost signals.

• Journal of Microbiology and Biotechnology
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• v.32 no.12
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• pp.1573-1582
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• 2022

In this study, we investigated the optimal conditions for 3D structure printing of alternative fats that have the textural properties of lard using beeswax (BW)-based oleogel by a statistical analysis. Products printed with over 15% BW oleogel at 50% and 75% infill level (IL) showed high printing accuracy with the lowest dimensional printing deviation for the designed model. The hardness, cohesion, and adhesion of printed samples were influenced by BW concentration and infill level. For multi-response optimization, fixed target values (hardness, adhesiveness, and cohesiveness) were applied with lard printed at 75% IL. The preparation parameters obtained as a result of multiple reaction prediction were 58.9% IL and 16.0% BW, and printing with this oleogel achieved fixed target values similar to those of lard. In conclusion, our study shows that 3D printing based on the BW oleogel system produces complex internal structures that allow adjustment of the textural properties of the printed samples, and BW oleogels could potentially serve as an excellent replacement for fat.