• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1996년도 추계학술발표회논문집(1)
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• pp.21-26
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• 1996

The identification of radioactive source in a medium with a limited number of external detectors is introduced as an inverse radiation transport problem. This kind of inverse problem is usually ill-posed and severely under-determined, however, its applications are very useful in manu fields including medical diagnosis and nondestructive assay of nuclear materials. Therefore, it is desired to develop efficient and robust solution algorithms. As an approach to solving inverse problems, an artificial neural network is proposed. We develop a modified version of the conventional Hopfield neural network and demonstrate its efficiency and robustness.

• 한국경영과학회지
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• 제35권2호
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• pp.53-69
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• 2010

This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therefore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.53-55
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• 2006

This paper presents self tuning PI controller of IPMSM drive using neural network. NNPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of Information Processing Systems
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• 제4권2호
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• pp.77-86
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• 2008

This research proposes a new neural network for text categorization which uses alternative representations of documents to numerical vectors. Since the proposed neural network is intended originally only for text categorization, it is called NTC (Neural Text Categorizer) in this research. Numerical vectors representing documents for tasks of text mining have inherently two main problems: huge dimensionality and sparse distribution. Although many various feature selection methods are developed to address the first problem, the reduced dimension remains still large. If the dimension is reduced excessively by a feature selection method, robustness of text categorization is degraded. Even if SVM (Support Vector Machine) is tolerable to huge dimensionality, it is not so to the second problem. The goal of this research is to address the two problems at same time by proposing a new representation of documents and a new neural network using the representation for its input vector.

• 제어로봇시스템학회논문지
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• 제8권4호
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• pp.281-287
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• 2002

This paper investigates on the feasibility of fuzzy logic control for networked control systems. In order to evaluate its feasibility, a networked control system for motor speed control is implemented on a Profibus-DP network. The NCS consists of several inde-pendent, but interacting processes running on two separate stations. By using this NCS, the network-induced delay is analyzed to find the cause and effect of the delay. Furthermore, in order to prove the feasibility, the fuzzy logic controller's performance is compared with those of conventional PID controllers. Based on the experimental results, the fuzzy logic controller can be a viable choice far NCS due to its robustness against parameter uncertainty.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.917-924
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• 2018

Recently, researches using LBP and SVM have been performed as one of the image - based methods for facial emotion recognition. LBP, introduced by Ojala et al., is widely used in the field of image recognition due to its high discrimination of objects, robustness to illumination change, and simple operation. In addition, CS(Center-Symmetric)-LBP was used as a modified form of LBP, which is widely used for face recognition. In this paper, we propose a method to detect four facial expressions such as expressionless, happiness, surprise, and anger using deep neural network. The validity of the proposed method is verified using accuracy. Based on the existing LBP feature parameters, it was confirmed that the method using the deep neural network is superior to the method using the Adaboost and SVM classifier.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.797-799
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• 2000

Most neural network learning schemes are derived from learning systems which are generally iterative in nature. But, when the given input-output training vector pairs satisfy a PLI condition, the training and the application of a hard-limited neural network can be achieved non-iteratively with very short training time and very robust recognition when it is applied to recognize any untrained patterns. In this paper, a method of expanding the dimension of training pattern data is suggested. The proposed method demonstrates better performance and robustness.

• Journal of information and communication convergence engineering
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• 제8권3호
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• pp.333-338
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• 2010

This paper derives a nominal state relationship (NSR) from the data of a nominal system. Through an example of a second order system, it is shown that the relationship can be derived only in the system with different real eigenvalues. In higher order system, the relationship is expressed by using neural network (NN). The derived NSR is used to design a noble sliding surface with a nominal system characteristic. By using the sliding surface, the robustness of the sliding mode control (SMC) is added to the pole-placement control.

• 한국통신학회논문지
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• 제18권3호
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• pp.360-371
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• 1993

Flooding 탐색 알고리즘은 고도의 생존성과 신뢰성이 있으므로 전술응용을 위한 효과적 라우팅 메커니즘이라고 알려져 있다. 그러나 망 효율성 측면에서는 큰 결점을 갖고 있다. 본 논문에서는 음성 트래픽에 대하여 최대 4개의 링크와 2개의 우선순위클래스를 갖는 전술 회선교환 격자망을 MFDL 경로기법을 사용하여 호설정시간 증가 및 알고리즘의 프로세서로딩없이 회선교환망의 블로킹 확률에 대한 성능개선 방법을 제안하였다.

• Journal of Communications and Networks
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• 제16권3호
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• pp.311-321
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• 2014

This paper focuses on contention-based medium access control (MAC) protocols used in wireless local area networks. We propose a novel MAC protocol called adaptive backoff tuning MAC (ABTMAC) based on IEEE 802.11 distributed coordination function (DCF). In our proposed MAC protocol, we utilize a fixed transmission attempt rate and each node dynamically adjusts its backoff window size considering the current network status. We determined the appropriate transmission attempt rate for both cases where the request-to-send/clear-to-send mechanism was and was not employed. Robustness against performance degradation caused by the difference between desired and actual values of the attempt rate parameter is considered when setting it. The performance of the protocol is evaluated analytically and through simulations. These results indicate that a wireless network utilizing ABTMAC performs better than one using IEEE 802.11 DCF.