• Journal of KIBIM
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• v.12 no.1
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• pp.62-71
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• 2022

In order to overcome the limitations of th 2D method regardless of the client's request, the application of BIM was reviewed to create hight-quality products using 3D models and various BIM information for offshore wind jacket-type structures. First, we defined the input value through analysis of the target structure and wrote an algorithm(script library) and library to complete the BIM model. Design review using geometry information based on th BIM model, usage for visualization drawings and quantity calculation were reviewed. For the purpose of initial review, only libraries with a limited number of subjects limitations on the scope of research were used. However, in the futrue, various libraries will be developed and research will be conducted to expand the scope of subjects.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.146-158
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• 2022

With the success of the digital economy and the rapid development of its technology, network security has received increasing attention. Intrusion detection technology has always been a focus and hotspot of research. A hybrid model that combines particle swarm optimization (PSO) and kernel extreme learning machine (KELM) is presented in this work. Continuous-valued PSO and binary PSO (BPSO) are adopted together to determine the parameter combination and the feature subset. A fitness function based on the detection rate and the number of selected features is proposed. The results show that the method can simultaneously determine the parameter values and select features. Furthermore, competitive or better accuracy can be obtained using approximately one quarter of the raw input features. Experiments proved that our method is slightly better than the genetic algorithm-based KELM model.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.30-36
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• 2000

The hidden node plays a role of the functional units that classifies the features of input pattern in the given question. Therefore, a neural network that consists of the number of a suitable optimum hidden node has be on the rise as a factor that has an important effect upon a result. However there is a problem that decides the number of hidden nodes based on back-propagation learning algorithm. If the number of hidden nodes is designated very small perfect learning is not done because the input pattern given cannot be classified enough. On the other hand, if designated a lot, overfitting occurs due to the unnecessary execution of operation and extravagance of memory point. So, the recognition rate is been law and the generality is fallen. Therefore, this paper suggests a method that decides the number of neural network node with feature information consisted of the parameter of learning algorithm. It excludes a node in the Pruning target, that has a maximum value among the feature value obtained and compares the average of the rest of hidden node feature value with the feature value of each hidden node, and then would like to improve the learning speed of neural network deciding the optimum structure of the multi-layer neural network as pruning the hidden node that has the feature value smaller than the average.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.495-508
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• 2004

Recently, in content-based music information retrieval systems, to enhance the response time of retrieving music data from large music database, some researches have adopted the indexing mechanism that extracts and indexes the representative melodies. The representative melody of music data must stand for the music itself and have strong possibility to use as users' input queries. However, since the previous researches have not considered the musical composition forms, they are not able to correctly catch the contrast, repetition and variation of motif in musical forms. In this paper, we use an index automatically constructed from representative melodies such like first melody, climax melodies and similarly repeated theme melodies. At first, we expand the clustering algorithm in order to extract similarly repeated theme melodies based on the musical composition forms. If the first melody and climax melodies are not included into the representative melodies of music by the clustering algorithm, we add them into representative melodies. We implemented a prototype system and did experiments on comparison the representative melody index with other melody indexes. Since, we are able to construct the representative melody index with the lower storage by 34％ than whole melody index, the response time can be decreased. Also, since we include first melody and climax melody which have the strong possibility to use as users' input query into representative melodies, we are able to get the more correct results against the various users' input queries than theme melody index with the cost of storage overhead of 20％.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.155-164
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• 2014

Local histogram equalization is one of the most popular ways of enhancing the local brightness features of an input image. However, local histogram equalization reveals some problems. First, undesired artifacts are produced by over-enhancing the local features. Second, the enhancement of local features does not always result in global contrast enhancement. To cope with these problems, we propose an illumination driven local histogram equalization method. First, to estimate the illumination information, the proposed method combines the input image and the blurred image produced through the process of the down-sampling and the up-sampling. Next, the proposed method adaptively adjusts the mapping function estimated by the local histogram equalization using the information of the illumination. As a result, the proposed illumination information driven local histogram equalization method simultaneously enhances the global and the local contrast levels while preventing any local artifacts. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1638-1643
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• 2019

In this paper, we propose an adaptive-perturbation-aided opportunistic precoding (APOP) scheme for multiple-input multiple-output (MIMO) systems. To update a precoding matrix in MIMO systems, the proposed algorithm produces a random perturbation in each time slot. Then the additional adaptive perturbation is also applied, which depends on the reports of achievable data-rates from users. If the prior random perturbation increased the data rate, the adaptive perturbation is set to be the same as the prior random perturbation, otherwise the negative value of the prior random perturbation is applied for adaptive perturbation. Furthermore, to enhance the achievable data rates, the information on the stored precoding matrices in the memory as well as the currently generated precoding matrix is used for scheduling. Simulation results show that compared to conventional opportunistic precoding schemes, higher data rates are achieved by the proposed APOP scheme, especially when there are a relatively small number of users.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.1
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• pp.59-67
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• 2009

In this paper, we have proposed the structure of the IMADF(improved modified multiplication-free adaptive filter) to cancel the adaptive noise in biomedical signals. The IMADF structure use the one-step predicted filter in the multiplication-free adaptive digital filter(MADF) structure using the DPCM and Sign algorithm. And then we use the heart phantom model based on the magnetocardiographic (MCG) to test the biomedical signals and analyze the signal of it. Their functions of the heart phantom occur from the multidipole current source. This can play role the same in the real function of the human heart to study it. In the experimental results, the IMADF algorithm has reduced the computational complexity by use of only the addition operation without a multiplier. Also, under the condition of identical stationary-state error, it could obtain the stabled convergence characteristics that the IMADF algorithm is almost same as the sign algorithm, but is better than the MADF algorithm. Here, this algorithm has effective characteristics when the correlation of the input signal is highly.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.325-330
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• 2004

The Big O notation of a sorting algorithm analysis is an asymptotic algorithm analysis which gives information of a rough mathematical function with an infinite increase of a sample size, without any specification of a probabilistic model. Hence. in an application with a limited finite number of data, it is necessary to test efficiencies of sorting algorithms. I estimated probabilistic models which analyze the number of exchanges varying input sizes to sort. The estimated models to explain the relationship of sorting efficiency on the sample size (N of the sample size and S of the number of exchange of elements) are S=0.9305 $N^{1.339}$ for Quick sort algorithm with O(nlogn) time complexity, and S=0.2232 $N^{2.0130}$ for Insertion sort algorithm with O( $n^2$) time complexity. Furthermore, there are strongly supports that more than 99% of the above relationship could be explained by the estimated models (p＜0.001). These findings suggest it is necessary to analyze sorting algorithm efficiency in applications with a finite number of data or a newly developed sorting algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.9
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• pp.37-43
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• 2010

An Interference Cancellation Wireless Repeater transmitts directly amplified the RF signal input to extend the coverage of the base station. Such a repeater inevitably suffers from the feedback interferences due to the environment and the adaptive Interference Cancelling System(ICS) is necessary. In this paper, the Variable Stepsize Complex Sign -Sign(VSCSS) LMS algorithm for ICS is presented. The algorithm can be implemented without multiplication/division arithmetic operation so that the required logic resources can be dramatically reduced in FPGA implementation. The performance of the proposed algorithm was analyzed in comparison with CSS-LMS algorithm and the learning curves obtained from simulation showed an excellent agreement with the theorical prediction. The simulation result with ICS in fading feedback channel environment showed the performance of the proposed algorithm is competible with NLMS algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.93-113
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• 2020

According to information theory, non-orthogonal transmission can achieve the multiple-user channel capacity with an onion-peeling like successive interference cancellation (SIC) based detection followed by a capacity approaching channel code. However, in multiple antenna system, due to the unideal characteristic of the SIC detector, the residual interference propagated to the next detection stage will significantly degrade the detection performance of spatial data layers. To overcome this problem, we proposed a modified power-domain non-orthogonal multiple access (P-NOMA) scheme joint designed with space-time coding for multiple input multiple output (MIMO) NOMA system. First, with proper power allocation for each user, inter-user signals can be separated from each other for NOMA detection. Second, a well-designed quasi-orthogonal space-time block code (QO-STBC) was employed to facilitate the SIC-based MIMO detection of spatial data layers within each user. Last, we proposed an optimization algorithm to assign channel coding rates to balance the bit error rate (BER) performance of those spatial data layers for each user. Link-level performance simulation results demonstrate that the proposed time-space-power domain joint transmission scheme performs better than the traditional P-NOMA scheme. Furthermore, the proposed algorithm is of low complexity and easy to implement.