• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.848-857
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• 2011

Vision-based collision avoidance system for air traffic management requires a excellent multiple target detection algorithm under low signal-to-noise ratio (SNR) levels. The track-before-detect (TBD) approaches have significant applications such as detection of small and dim targets from an image sequence. In this paper, two detection algorithms with the TBD approaches are proposed to satisfy the multiple target detection requirements. The first algorithm, based on a dynamic programming approach, is designed to classify multiple targets by using a k-means clustering algorithm. In the second approach, a hidden Markov model (HMM) is slightly modified for detecting multiple targets sequentially. Both of the proposed approaches are used in numerical simulations with variations in target appearance properties to provide satisfactory performance as multiple target detection methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• The Journal of Society for e-Business Studies
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• v.23 no.3
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• pp.225-237
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• 2018

The demand for processing large data streams is growing rapidly as the generation and processing of large volumes of data become more popular. A variety of large data processing technologies are being developed to suit the increasing demand. One of the technologies that researchers have particularly observed is the data stream clustering with sliding windows. Data stream clustering with sliding windows may create a new set of clusters whenever the window moves. Previous data stream clustering techniques with sliding windows exploit the coresets, also known as group features that summarize the data. In this paper, we present some reformable elements of a group-feature based algorithm, and propose our algorithm that modified the clustering algorithm of the original one. We conduct a performance comparison between two algorithms by using different parameter values. Finally, we provide some guideline for the selective use of those algorithms with regard to the parameter values and their impacts on the performance.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.1-8
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• 1996

Recently, much attention has been paid to problems which is concerned with voltage instability phenomena and much works on these phenomena have been made. In this paper, by substituting d $P_{k}$ d $e_{k}$ ( $v^{\rarw}$= e +j f) for $P_{k}$ in conventional load flow, direct method for finging the limit of voltage stability is proposed. Here, by using the fact that taylor se- ries expansion in .DELTA. $P_{k}$ and .DELTA. $Q_{k}$ is terminated at the second-order terms, constraint equation (d $P_{k}$ d $e_{k}$ =0) and power flow equations are formulated with new variables .DSLTA. e and .DELTA.f, so partial differentiations for constraint equation are precisely calculated. The fact that iteratively calculated equations are reformulated with new variables .DELTA.e and .DELTA.f means that limit of voltage stability can be traced precisely through recalculation of jacobian matrix at e+.DELTA.e and f+.DELTA.f state. Then, during iterative process divergence may be avoid. Also, as elements of Hessian mat rix are constant, its computations are required only once during iterative process. Results of application of the proposed method to sample systems are presented. (author). 13 refs., 11 figs., 4 tab.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.12
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• pp.1759-1771
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• 2017

In this paper, an improved continuous integral variable structure systems(ICIVSS) with the prescribed control performance is designed for simple regulation controls of uncertain general linear systems. An integral sliding surface with an integral state having a special initial condition is adopted for removing the reaching phase and predetermining the ideal sliding trajectory from a given initial state to the origin in the state space. The ideal sliding dynamics of the integral sliding surface is analytically obtained and the solution of the ideal sliding dynamics can predetermine the ideal sliding trajectory(integral sliding surface) from the given initial state to the origin. Provided that the value of the integral sliding surface is bounded by certain value by means of the continuous input, the norm of the state error to the ideal sliding trajectory is analyzed and obtained in Theorem 1. A corresponding discontinuous control input with the exponential stability is proposed to generate the perfect sliding mode on the every point of the pre-selected sliding surface. For practical applications, the discontinuity of the VSS control input is approximated to be continuous based on the proposed modified fixed boundary layer method. The bounded stability by the continuous input is investigated in Theorem 3. With combining the results of Theorem 1 and Theorem 3, as the prescribed control performance, the pre specification on the error to the ideal sliding trajectory is possible by means of the boundary layer continuous input with the integral sliding surface. The suggested algorithm with the continuous input can provide the effective method to increase the control accuracy within the boundary layer by means of the increase of the $G_1$ gain. Through an illustrative design example and simulation study, the usefulness of the main results is verified.

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.414-428
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• 2004

Many portable devices are coming to be commercially successful and provide useful services to mobile users. Mobile devices may request a variety of data types, including text and multimedia data, thanks to the rich content of the Internet. Different types of data and/or different classes of users may need to be treated with different qualities of service. The implementation of service differentiation in wireless networks is very difficult because of device mobility and wireless channel contention when the backoff algorithm is used to resolve contention. Modification of the t)mary exponential backoff algorithm is one possibility to allow the design of several classes of data traffic flows. We present a study of modifications to the backoff algorithm to support three classes of flows: sold, silver, and bronze. For example, the gold c]ass flows are the highest priority and should satisfy their required target bandwidth, whereas the silver class flows should receive reasonably high bandwidth compared to the bronze class flows. The mixture of the two different transport protocols, UDP and TCP, in ad hoc networks raises significant challenges when defining backoff algorithm modifications. Due to the different characteristics of UDP and TCP, different backoff algorithm modifications are applied to each class of packets from the two transport protocols. Nevertheless, we show by means of simulation that our approach of backoff algorithm modification clearly differentiates service between different flows of classes regardless of the type of transport protocol.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.367-369
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• 2002

We have designed ramp profile excitation pulse based on the Shinnar-Le Roux (SLR) algorithm. The algorithm provides many advantages to pulse designers. The first advantage is the freedom of deciding the amplitudes, frequencies, and ripple sizes of stopband, passband, and transition band of pulse profile. The second advantage is the freedom of deciding the pulse phase, more specifically, minimum phase, linear phase, maximum phase, and any phase between them. The minimum phase pulse is the best choice in the case of 3D TOF, because it minimizes the echo time, which implies the best image quality in the same MR examination condition. In addition, the half echo technique is slightly modified in our case. In general, using the half echo technique means that the acquired data size is half and the rest part can be filled with complex conjugate of acquired data. But in our case, the echo center is just shifted to left, which implies the reduction of echo time, and the acquired data size is the same as the one without using the half echo technique. In this case, the increase of right part of data leads to improvement of the resolution and the decrease of left part of data leads to decrease of signal to noise ratio. Since in the case of 3D TOF, the signal to noise ratio is sufficiently high and the resolution is more important than signal to noise ratio, the proposed method appears to be significantly affective and gives rise to the improved high resolution angiograms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.231-241
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• 2005

New methods to register multiple hemispheric slices of the postmortem brain to anatomically corresponding in-vivo MRI slices within a 3D volumetric MRI are presented. Gel-embedding and fiducial markers are used to reduce geometrical distortions in the postmortem brain volume. The registration algorithm relies on a recursive extraction of warped MRI slices from the reference MRI volume using a modified non-linear polynomial transformation until matching slices are found. Eight different voxel similarity measures are tested to get the best co-registration cost and the results show that combination of two different similarity measures shows the best performance. After validating the implementation and approach through simulation studies, the presented methods are applied to real data. The results demonstrate the feasibility and practicability of the presented co­registration methods, thus providing a means of MR signal analysis and histological examination of tissue lesions via co­registered images of postmortem brain slices and their corresponding MRI sections. With this approach, it is possible to investigate the pathology of a disease through both routinely acquired MRls and postmortem brain slices, thus improving the understanding of the pathological substrates and their progression.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.3-11
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• 2014

Recently, rapid urbanization has necessitated continuous updates in digital map to provide the latest and accurate information for users. However, conventional aerial photogrammetry has some restrictions on periodic updates of small areas due to high cost, and as-built drawing also brings some problems with maintaining quality. Alternatively, this paper proposes a scheme for efficient and accurate update of digital map using point cloud data acquired by Terrestrial Laser Scanner (TLS). Initially, from the whole point cloud data, the building sides are extracted and projected onto a 2D image to trace out the 2D building footprints. In order to register the footprint extractions on the digital map, 2D Affine model is used. For Affine parameter estimation, the centroids of each footprint groups are randomly chosen and matched by means of a modified RANSAC algorithm. Based on proposed algorithm, the experimental results showed that it is possible to renew digital map using building footprint extracted from TLS data.