• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.5
• /
• pp.525-530
• /
• 2006

This paper presents an efficient input variable selection method using both fixed-point independent component analysis(FP-ICA) and adaptive partition mutual information(AP-MI) estimation. FP-ICA which is based on secant method, is applied to quickly find the independence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function(PDF). The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the FP-ICA and regular partition MI estimation.

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04a
• /
• pp.892-894
• /
• 2004

본 논문은 신인상주의(Neo-impressionism)의 분할적, 점묘적인 화풍을 표현하기 위한 회화적 렌더링(painterly rendering)의 알고리즘과 그 구현 방법을 다루고 있다. 논문에서 제시하는 알고리즘은 한 장의 영상을 입력으로 하여, 신인상주의 화가인 쇠라(Georges Seurat)나 시냑(Paul Signac)의 점묘화 같은 느낌을 주는 결과 영상을 만들어 낸다. 결과 화면은 두 단계로 구성되며 입력 영상에서 색을 분할된 영상, 색이 분할된 영상을 이용하여 브러시 스트로크를 생성하여 적응시킨 결과 영상으로 이루어진다.

• Journal of KIISE:Software and Applications
• /
• v.36 no.6
• /
• pp.451-461
• /
• 2009

The Adaptive Random Testing(ART) aims to improve the performance of traditional Random Testing(RT) by reducing the number of test cases to find the failure region which is located in the input domain. Such enhancement can be obtained by efficient selection algorithms of test cases. The ART through Iterative Partitioning(IP-ART) is one of ART techniques and it uses an iterative input domain partitioning method to improve the performance of early-versions of ART which have significant drawbacks in computation time. And the IP-ART with Enlarged Input Domain(EIP-ART), an improved version of IP-ART, is known to make additional performance improvement with scalability by expanding to virtual test space beyond real input domain of IP-ART. The EIP-ART algorithm, however, have the drawback of heavy cost of computation time to generate test cases mainly due to the virtual input domain enlargement. For this reason, two algorithms are proposed in this paper to mitigate the computation overhead of the EIP-ART. In the experiments by simulations, the tiling technique of input domain, one of two proposed algorithms, showed significant improvements in terms of computation time and testing performance.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.9
• /
• pp.315-320
• /
• 2015

In cloud computing, server virtualization supports one or more virtual machines loaded on multiple operating systems on a single physical host server. Migration of a VM is moving the VM running on a source host to another physical machine called target host. A VM live migration is essential to support task performance optimization, energy efficiency and energy saving, fault tolerance and load balancing. In this paper, we propose open source based adaptive VM live migration technique. For this, we design VM monitoring module to decide VM live migration and open source based full-virtualization hypervisor.

• Journal of KIISE:Information Networking
• /
• v.31 no.3
• /
• pp.305-313
• /
• 2004

The use of a cache for a storing and processing of Web object is becoming larger. Also, many studies for efficient management of storing scope on cache are performed actively. Web caching technique have many differences with traditional techniques. Particularly, a heterogeneity of Web object which is a processing unit of Web caching and a variation of Web object reference characteristic with time are the important causes to decrease performance of existing techniques. In this study, We proposed the ACASH which was new web caching technique. As ACASH divided and managed Web object and a cache scope with a heterogeneity, It can reduced a heterogeneity variation of an object. Also, it is reflecting a variation of object reference characteristics with time adaptively. In the experiment, We verified that the performance of ACASH was improved than existing techniques on the two experiment model which considered a heterogeneity of an object.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2007.04a
• /
• pp.382-385
• /
• 2007

본 논문에서는 다중 표적의 중첩이라는 상황에 대한 새로운 해결 방식을 소개한다. 비선형 표적의 위치와 속도에 대한 추적을 중심으로 표적과 비표적의 중첩이 일어나는 순간 이후 분리되었을 때 추적중인 표적을 지속적으로 유지할 수 있는 방법에 대해 이야기 하고자 한다. 이 논문에서 제안된 알고리즘은 예측 명중위치 개념과 최대 잡음수준을 이용한 칼만필터 기반의 적응 상호작용 다중모델 기법으로 측정된 위치값과 예측된 명중위치 사이의 차이를 고려한 변형된 칼만필터 개념을 이용한다. 이 논문에서는 비선형 표적의 가속도를 시변 변수인 표적의 추가적인 잡음으로 두고 각각의 가속도 간격의 정도에 따라 얻어지는 모든 잡음에 대한 변수에 의해 각각의 하부 모델들을 특성화시켰다. 제안된 알고리즘은 표적의 운동특성에 따라 적응적으로 기법을 선택할 수 있는 선택적 방식을 구현하고자 한다. 표적의 기동중에 나타나는 가속도를 효과적으로 다루기 위하여 잡음의 크기가 급격히 증가하는 경우 그 증가분을 가속도로 인식하여 기동표적 관계식에 이용한다. 그리고 제안된 알고리즘의 수행 가능성을 보여주기 위하여 몇 가지 예를 제시하였다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.5
• /
• pp.817-824
• /
• 2019

We propose an ATR (Adaptive Tone Reservation) scheme based on clipping noise for PAPR (Peak-to-Average Power Ratio) reduction of OFDM (Orthogonal Frequency Division Multiplexing) signals. The proposed scheme is composed of three steps: clipping, tone selection, and TR procedures. In the first step, the peak samples in the IFFT (Inverse Fast Fourier Transform) outputs are scaled down by clipping. In the second step, the sub-carrier position where the power of the clipping noise is the maximum, is selected. Finally, the generic TR procedure is performed. Simulation results show that the proposed scheme does not require all the possible combinations for the original TR procedures, while maintaining the PAPR reduction performance.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.3
• /
• pp.18-27
• /
• 2009

In this paper, we propose a frame rate conversion algorithm using adaptive search-based motion estimation (ME). The proposed ME method uses recursive search, 3-step search, and single predicted search as candidates for search strategy. The best method among the three candidates is adaptively selected on a block basis according to the predicted motion type. The adaptation of the search method improves the accuracy of the estimated motion vectors while curbing the increase of computational load. To support the proposed ME method, an entire image is divided into three regions with different motion types. Experimental results show that the proposed FRC method achieves better image quality than existing algorithms in both subjective and objective measures.

• Journal of KIISE:Information Networking
• /
• v.30 no.2
• /
• pp.155-166
• /
• 2003

Mobile computing becomes a new issue of researches in computing due to the advances of mobile equipment and the connection with Internet. In mobile environment, there are many constraints such as limited bandwidth, intermittent disconnection, limited battery life, and so on. By these reasons, broadcasting has been generally used to disseminate data efficiently by the mobile applications. This paper proposes an adaptive broadcasting method which logically divides broadcast channel into the periodic broadcast channel and the on-demand broadcast channel and dynamically assigns the bandwidths of both channel. The former disseminates data that are selected based on both the popularity and the size of each datum, the latter disseminates data that are selected based on the requests of mobile clients. When selecting data to be disseminated, the proposed broadcasting method considers the mobility of a mobile client and also considers the size of each datum by using SF(size factor) proposed in this paper. This paper also evaluates the proposed broadcasting method by measuring the energy expenditure of mobile client in experiments.

• Journal of KIISE:Databases
• /
• v.31 no.2
• /
• pp.122-131
• /
• 2004

Traditional works on indexing have been suggested for low dimensional data under dynamic environments. But recent database applications require efficient processing of huge sire of high dimensional data under static environments. Thus many indexing strategies suggested especially in partitioning ones do not adapt to these new environments. In our study, we point out these facts and propose a new partitioning strategy, which complies with new applications' requirements and is derived from analysis. As a preliminary step to propose our method, we apply a packing technique on the one hand and exploit observations on the Minkowski-sum cost model on the other, under uniform data distribution. Observations predict that unbalanced partitioning strategy may be more query-efficient than balanced partitioning strategy for high dimensional data. Thus we propose our method, called CSP (Cyclic Spliced Partitioning method). Analysis on this method explicitly suggests metrics on how to partition high dimensional data. By the cost model, simulations, and experiments, we show excellent performance of our method over balanced strategy. By experimental studies on other indices and packing methods, we also show the superiority of our method.