• 한국통신학회논문지
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• 제37권2B호
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• pp.138-147
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• 2012

무선통신기술과 임베디드 기술의 발달로 무선 센서네트워크는 다양한 분야에서 활발하게 응용되고 있기는 하지만, 자원제약적 특성을 가지는 센서 노드와 네트워크 자체의 특성들로 인해 다른 네트워크에 비해 많은 보안 취약점들을 가지고 있다. 이러한 보안 문제를 해결하기위해 암호화나 인증 등의 전통적 보안 메커니즘을 활용할 수 있지만, 잠식된 노드에 의한 공격에는 전통적 보안 메커니즘만으로는 적절히 대응할 수 없다. 따라서 무선 센서네트워크의 적절한 보안환경을 위해서는 2차적 보안 메커니즘이 필요하며, 이는 침입탐지 시스템이 고려될 수 있다. 이에 본 논문에서는 무선 센서네트워크의 클러스터링 라우팅 프로토콜인 LEACH(Low Energy Adaptive Clustering Hierarchy)를 대상으로 하여 안전하고 신뢰성 있는 네트워크를 형성할 수 있도록 해 주는 명세기반의 침입탐지 기법을 제안한다.

• 한국지능시스템학회논문지
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• 제25권1호
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• pp.97-104
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• 2015

An 'associative cube', a class of auto-associative memories, is revisited here, in which training data and hidden orthogonal basis functions such as wavelet packets or Fourier kernels, are combined in the weight cube. This weight cube has hidden units in its depth, represented by a three dimensional cubic structure. We develop an unsupervised incremental learning mechanism based upon the adaptive least squares method. Training data are mapped into orthogonal basis vectors in a least-squares sense by updating the weights which minimize an energy function. Therefore, a prescribed orthogonal kernel is incrementally assigned to an incoming data. Next, we show how a decoding procedure finds the closest one with a competitive network in the hidden layer. As noisy test data are applied to an associative cube, the nearest one among the original training data are restored in an optimal sense. The simulation results confirm robustness of associative cubes even if test data are heavily distorted by various types of noise.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1295-1298
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• 2004

Selective Laser Sintering(SLS) method is one of Rapid Prototyping(RP) technologies. It is used to fabricate desirable part to sinter powder and stack the fabricated layer. To develop this SLS machine, it needs effective scanning path and the development of scanning device. This paper shows how to make fast scanning path with respect to scan spacing, laser beam size and scanning direction from 2-dimensional sliced file generated in commercial CAD/CAM software. Also, we develop the scanning device and its control algorithm to precisely follow the generated scanning path. Scanning path affects precision and total machining time of the final fabricated part. Sintering occurs using infrared laser which has high thermal energy. As a result, shrinkage and curling of the fabricated part occurs according to thermal distribution. Therefore, fast scanning path generation is needed to eliminate the factors of quality deterioration. It highly affects machining efficiency and prevents shrinkage and curling by relatively lessening the thermal distribution of the surface of sintering layer. To generate this fast scanning path, adaptive path generation is needed with respect to the shape of each layer, and not simply x, y scanning, but the scanning of arbitrary direction must be enabled. This paper addresses path generation method to focus on fast scanning, and development of scanning system and control algorithm to precisely follow generated path.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 추계학술대회 논문집
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• pp.359-362
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using multi adaptive fuzzy learning controller(AFLC). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 한국군사과학기술학회지
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• 제15권3호
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• pp.322-333
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

• 대한음성학회지:말소리
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• 제57호
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• pp.175-189
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• 2006

Because a packet loss brings about degradation of speech quality, VoIP speech coders have PLC (Packet Loss Concealment) mechanism. G.711, which is a mandatory VoIP speech coder, also has the PLC algorithm based on pitch period replication. However, it is not robust to burst losses. Thus, we propose two methods to improve the performance of the original PLC algorithm in G.711. One adaptively utilizes voiced/unvoiced information of adjacent good frames regarding to the current lost frame. The other is based on adaptive gain control according to energy variation across the frames. We evaluate the performance of the proposed PLC algorithm by measuring a PESQ value under different random and burst packet loss simulating conditions. It is shown from the experiments that the performance of the proposed PLC algorithm outperforms that of PLC employed in ITU-T Recommendation G.711.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.776_777
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• 2009

Optimal efficiency control of synchronous reluctance motor(SynRM) is very important in the sense of energy saving and conservation of natural environment because the efficiency of the SynRM is generally lower than that of other types of AC motors. This paper is proposed a novel efficiency optimization control of SynRM considering iron loss using neural network(NN). The optimal current ratio between torque current and exciting current is analytically derived to drive SynRM at maximum efficiency. This paper is proposed an efficiency optimization control for the SynRM which minimizes the copper and iron losses. The design of the speed controller based on adaptive learning mechanism fuzzy-neural networks(ALM-FNN) controller that is implemented using fuzzy control and neural networks. The objective of the efficiency optimization control is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. The control performance of the proposed controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.

• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.294-305
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• 2009

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

• 한국군사과학기술학회지
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• 제23권1호
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• pp.43-51
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• 2020

In this study, numerical analysis was carried out on a complex pressure field of blast waves caused by the detonation of high explosives in various environments. The generated blast waves propagated in the air, upon the sudden release of high energy induced by the explosion. Reflected waves were created when the pressure waves encountered certain obstacles such as the ground or the walls of structures. The propagation of the blast waves and its interaction with the reflected waves were simulated. An adaptive mesh refinement was applied to improve the efficiency of distribution of computer resource, for the computational calculation of the blast wave propagation in a wide open space. In addition, the integration of the calculation domains for the explosive and air were considered when the maximum density of the explosive region was below critical value. The results were verified by comparison with the pressure time history from blast wave experiments performed under two topographical conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.2099-2100
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• 2006

제한된 전력의 노드들로 구성된 무선 센서 네트워크에서 효율적인 정보 수집이 이루어지기 위해서는 전체 네트워크의 Life Time을 늘리는 게 중요하다. 각각의 센서 노드들이 멀리 떨어져 있는 BS(Base Station)으로 직접 데이터를 전송하면 전력소비가 매우 크고 비효율 적이다. 그리하여 네트워크의 life time을 늘리기 위한 많은 연구가 이루어지고 있다. 그중에 클러스터링 기법은 가장 널리 연구되는 기법 중에 하나이다. 대표적인 클러스터링 기법 LEACH(Low-Energy Adaptive Clustering Hierarchy)[1]는 전체 노드 수의 5%클 클러스터 헤드로 결정하여 나머지 노드들로부터 데이터를 수집하여 BS로 전송함으로써 에너지를 효율적으로 사용하는 알고리즘이다. 그러나 클러스터 헤드를 결정하는데 있어서 잔여 에너지를 고려하지 않고 순환적으로 결정하는 문제점을 가지고 있다. 그래서 본 논문에서는 SVM(Supprt Vector Machine)을 이용하여 FND(First Node Dic)가 발생했을 때 각 노드들의 에너지 잔량 정도를 따져서 영역을 나눈 후, 에너지가 더 많은 영역에서 클러스터 헤드를 선정하는 방법을 제안한다. 잔량 에너지가 많은 노드를 클러스터 헤드로 결정함으로써 전체 네트워크의 life time을 늘릴 수 있다.