• Journal of KIISE:Databases
• /
• v.31 no.4
• /
• pp.422-431
• /
• 2004

In recent years, different models in data delivery have been explored in mobile computing systems. Particularly, there were a lot of research efforts in the periodic push model where the server repetitively disseminates information without explicit request. However, average waiting time per data operation highly depends on the length of a broadcast cycle and different access pattern among clients may deteriorate the response time considerably. In this case, clients are preferably willing to send a data request to the server explicitly through backchannel in order to obtain optimal response time. We call the broadcast model supporting backchannel as hybrid broadcast. In this paper, we devise a new transaction processing algorithm(O-PreH) in hybrid broadcast environments. The data objects which the server maintains are divided into Push_Data for periodic broadcasting and Pull_Data for on-demand processing. Clients tune in broadcast channel or demand the data of interests according to the data type. Periodic invalidation reports from the server support maintaining transactional consistency. If one or more conflicts are found, conflict orders are determined not to violate the consistency(pre-reordering) and then the remaining operations have to be executed pessimistically. Through extensive simulations, we demonstrate the improved throughput of the proposed algorithm.

• The KIPS Transactions:PartC
• /
• v.16C no.2
• /
• pp.199-208
• /
• 2009

Recently,IP-based broadcasting systems,such as Mobile-TV and IP-TV, have been widely deployed. These systems require a security system to allow only authorized subscribers access to broadcasting services. We analyzed the Conditional Access System, which is a security system used in the IP-based Pay-TV systems. A weakness of the system is that it does not scale well when the system experiences frequent membership changes. In this paper, we propose a group key distribution protocol which overcomes the scalability problem by reducing communication and computation overheads without loss of security strength. Our experimental results show that computation delay of the proposed protocol is smaller than one of the Conditional Access System. This is attributed to the fact that the proposed protocol replaces expensive encryption and decryption with relatively inexpensive arithmetic operations. In addition, the proposed protocol can help to set up a secure channel between a server and a client with the minimum additional overhead.

• Smart Media Journal
• /
• v.5 no.3
• /
• pp.35-41
• /
• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• KIISE Transactions on Computing Practices
• /
• v.22 no.8
• /
• pp.357-362
• /
• 2016

A social network or bio network is one of the complex networks that are formed by connecting specific relationships between interacting objects. Usually, these networks consist of community structures. Automatically detecting the structures is an important technique to understand and control the interaction objects. However, the topologies and structures of the networks change by interactions of the objects, with respect to time. Conventional techniques for finding the community structure have a high computational complexity. Additionally, the methods inefficiently deal with repeated computation concerning graph operation. In this paper, we propose an incremental technique for detecting interaction-based communities in dynamic networks. The proposed technique is able to efficiently find the communities, since there is an awareness of changed objects from the previous network, and it can incrementally reuse the previous community structure.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.2
• /
• pp.279-286
• /
• 2015

EMD is a fully data-driven signal processing method without using any predetermined basis function and requiring any user parameters setting. However EMD experiences a problem of mode mixing which interferes with decomposing the signal into similar oscillations within a mode. To overcome the problem, EEMD method was introduced. The algorithm performs the EMD method over an ensemble of the signal added independent identically distributed white noise of the same standard deviation. Even so EEMD created problems when the decomposition is complete. The ensemble of different signal with added noise may produce different number of modes and the reconstructed signal includes residual noise. This paper propose an modified EEMD method to overcome mode mixing of EMD, to provide an exact reconstruction of the original signal, and to separate modes with lower cost than EEMD's. The experimental results show that the proposed method provides a better separation of the modes with less number of sifting iterations, costs 20.87% for a complete decomposition of the signal and demonstrates superior performance in the signal reconstruction, compared with EEMD.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.10
• /
• pp.487-492
• /
• 2017

Clustering is a technique which is used to measure similarities between data in big data analysis and data mining field. Among various clustering methods, k-Modes algorithm is representatively used for categorical data. To increase the performance of iterative-centric tasks such as k-Modes, a distributed and concurrent framework Spark has been received great attention recently because it overcomes the limitation of Hadoop. Spark provides an environment that can process large amount of data in main memory using the concept of abstract objects called RDD. Spark provides Mllib, a dedicated library for machine learning, but Mllib only includes k-means that can process only continuous data, so there is a limitation that categorical data processing is impossible. In this paper, we design RDD for k-Modes algorithm for categorical data clustering in spark environment and implement an algorithm that can operate effectively. Experiments show that the proposed algorithm increases linearly in the spark environment.

• Korean Journal of Remote Sensing
• /
• v.13 no.2
• /
• pp.85-98
• /
• 1997

A geometric model of pushbroom-type linear CCD camera images is proposed in this paper. At present, this type of cameras are used for obtaining almost all kinds of high-resolution optical images from satellites. The proposed geometric model includes not only a forward transformation which is much more efficient. An inverse transformation function cannot be derived analytically in a closed form because the focal point of an image varies with time. In this paper, therefore, an iterative algorithm in which a focal point os converged to a given pixel position is proposed. Although the proposed model can be applied to any pushbroom-type linear CCD camera images, the geometric model of the high-resolution multi-spectral camera on-board KITSAT-3 is used in this paper as an example. The flight model of KITSAT-3 is in development currently and it is due to be launched late 1998.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.281-281
• /
• 2019

수리모형실험은 수로 내에서 장시간 파랑을 발생시킬 경우, 수로 내에 반사 파랑의 성분이 누적될 수 있어 상당한 계측 오차를 발생시킬 우려가 있어 수리모형실험 결과의 검증이 필요하다. 일반적으로 수리모형실험 결과의 검증을 위해서는 동일 실험을 무수히 반복하여 불확실성을 제거하거나 다양한 수리실험실에서 수리모형실험을 수행하고 결과를 분석하여 불확실성을 제거할 수 있다. 그러나 이는 엄청난 시간과 노력은 물론 막대한 실험비용이 소요되기 때문에 경제적으로 효용성이 매우 낮아 현실적으로 수행이 어렵다. 이에 비해 수치모형실험은 상대적으로 저렴한 비용으로 수행할 수 있으며, 다수의 실험을 수행하지 않아도 불확실성을 제거할 수 있어 수리모형실험의 검증에 효율적이다. 일반적으로 난류 거동을 동반하는 복잡한 구조물 주변의 흐름 해석에는 3차원 CFD 모형이 필요하다. 특히, 병렬연산이 가능한 CFD 모형을 활용하면 수리모형실험에서도 재현이 쉽지 않은 다양한 조건에 따른 복잡한 흐름을 해석할 수 있어 효용성이 점점 증가하고 있다. 그러나 복잡한 구조물이 존재하게 되면 구조물에 재현에 막대한 격자구조가 필요하여 현실적으로 적용이 쉽지 않다. 이에 대한 대안으로 복잡한 구조물을 비교적 큰 격자에서 재현할 수 있는 가상경계법을 활용하는 연구가 활발히 진행되고 있다. 가상경계법은 Navier-Stokes 방정식에서 유체 내에 존재하는 고체를 모멘텀 이론으로 대체하여 고려하는 기법으로 수치모델링 수행 시 매질을 유체만으로 구성할 수 있어 안정적으로 적용할 수 있는 것으로 알려져 있다. 본 과업에서는 다양한 분야에서 널리 활용되고 있는 3차원 CFD 모형인 OpenFOAM®기반으로 파랑해석에 필요한 경계조건을 계산할 수 있는 olaFlow를 활용하여 복잡한 구조물을 지나는 파랑해석을 수행하기 위해 가상경계법을 olaFlow에 도입한 수치 알고리즘을 개발하였다. 개발한 수치알고리즘을 활용하여 복잡한 구조를 수치모델에서 재현하였으며, 수치모델에 적용된 수치 알고리즘의 안정성에 대해 고찰하였다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2016.05a
• /
• pp.521-521
• /
• 2016

상수도 관망은 수원에서 수요절점까지 물을 안정적으로 공급하는 것을 목표로 한다. 상수도 관망의 최적설계는 수리학적 제한조건 (절점의 수압, 관로의 유속)을 만족하는 범위에서 비용을 최소화하는 설계안을 얻는 것으로 Savic and Walters (1997)는 유전 알고리즘 (Genetic Algorithms, Holland 1975)을 적용한 상수도 관망 설계 프로그램인 GANET를 제안하였고, Maier et al. (1996)은 개미군집알고리즘 (Ant Colony Optimization Algorithm, Dorigo et al. 1996)을 상수도 관망 최적설계에 적용한 후 그 결과가 유전 알고리즘에 비해 우수함을 증명하는 등 상수도 관망 최적설계에 관한 연구가 활발히 진행되어 오고 있다. 유전알고리즘은 선택, 교차, 돌연변이의 반복계산 과정을 통하여 최적해를 찾는 최적화 기법이다. 이 과정에서 결정변수는 유전자 (Gene)의 집합으로 표현되며, 염색체 (Chromosome) 내에서 근접한 유전 인자들은 일종의 Building Block을 형성하게 된다. Building Block은 좋은 해를 갖는 유전 인자를 높은 확률로 보관하여 지역해에 빠질 가능성을 줄이는 반면, 유전형 (Genotype)이 표현형 (Phenotype)을 충분히 모방하여 표현하지 못한 경우 오히려 최적해의 탐색을 방해할 수 있다는 한계점을 갖는다. 유전 알고리즘을 상수도 관망 최적설계에 적용하였을 때에도 이 한계점은 여실히 드러난다. 관로의 관경을 결정변수로 설정한 후 유전형으로 표현하였을 때, 관망도 상에서 근접하지 않은 두 관로가 염색체 내에서 연속으로 나열된다면 두 관로 간의 연관성이 실제보다 크게 고려되기 때문이다. 한편, 하모니써치 (Harmony Search, Geem et al. 2001) 알고리즘은 즉흥 연주 (Improvisation)를 통해 최상의 화음을 만들어내는 현상으로부터 착안하여 만들어진 최적화기법으로 연산 기법은 무작위선택, 기억회상, 피치조정 등으로 구성되어 있으며, 결정변수에 해당하는 연주자가 독립적으로 행동하며 해를 탐색한다는 점에서 유전알고리즘과 큰 차이를 갖는다. 본 연구에서는 유전알고리즘의 Building Block에 의해 발생하는 오류를 개선하고자, 상수도 관망 최적설계 연구에 많이 사용되는 Hanoi 관망 (Fujiwara and Khang 1990) 관로의 정렬 순서를 여러 가지 기준으로 설정하여 관망데이터를 구축한 후 하모니써치와 유전 알고리즘을 적용하여 최적화를 수행하였고 그 결과를 비교하였다. 그 결과 유전 알고리즘과 달리 하모니써치 알고리즘의 경우, 관로의 나열 순서와 상관없이 우수한 최적해 탐색 결과를 보이는 것을 확인할 수 있었다.

• Journal of the Society of Naval Architects of Korea
• /
• v.31 no.3
• /
• pp.80-86
• /
• 1994

A numerical method for simulations of inviscid incompressible flow fields around a ship advancing on the free surface is developed. A body fitted coordinate system, generated by numerically solving elliptic type partial differential equations is used to conform the ship and free surface configurations. Three dimensional Euler equations transformed to the non-staggered body fitted coordinate system are discretised by finite difference method. Time and spatial derivatives are discretised by forward and centered differencings, respectively, and artificial dissipations are added to discretised convection terms for improvements of numerical stability. At each time steps, free surface elevations are recomputed to satisfy nonlinear free surface conditions. Poisson equations for pressure field are solved iteratively and the velocity field for next time step is extrapolated. To verify the developed numerical method, flow fields around a Wigley model are simulated(Fn=0.250-0.408) and compared with experimental data to show good agreements.