• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.105-111
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• 2002

Presented is a Genetic Algorithm(GA) for dynamic partitioning an ATM LANE(LAN Emulation) network. LANE proves to be one of the best solutions to provide guaranteed Quality of Service(QoS) for mid-size campus or enterprise networks with a little modification of legacy LAN facilities. However, there are few researches on the efficient LANE network operations to deal with scalability issues arising from broadcast traffic delivery. To cope with this scalability issue, proposed is a decision model named LANE Partitioning Problem(LPP) which aims at partitioning the entire LANE network into multiple Emulated LANs(ELANs), each of which works as an independent virtual LAN.

• 전기학회논문지
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• 제59권9호
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• pp.1673-1679
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• 2010

A photovoltaic (PV) generator is significantly regarded as one important alternative of renewable energy systems recently. Fault detection and diagnosis of engineering dynamic systems is a fundamental issue to timely prevent unexpected damages in industry fields. This paper presents an intelligent monitoring approach and fault detection technique for PV generator systems by means of artificial neural network and statistical signal detection theory. We devise a multi-Fourier neural network model for representing dynamics of PV systems and apply a general likelihood ratio test (GLRT) approach for investigating our decision making algorithm in fault detection and diagnosis. We make use of a test-bed of ubiquitous sensor network (USN) based PV monitoring systems for testing our proposed fault detection methodology. Lastly, a real-time experiment is accomplished for demonstrating its reliability and practicability.

• 한국국방경영분석학회지
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• 제18권2호
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• pp.66-95
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• 1992

Shortest paths are one of the simplest and most widely used concepts in deterministic networks. A decison of troops movement route can be analyzed in the network with a shortest path algorithm. But in reality, the value of arcs can not be determined in the network by crisp numbers due to imprecision or fuzziness in parameters. To account for this reason, a fuzzy network should be considered. A fuzzy shortest path can be modeled by general fuzzy mathematical programming and solved by fuzzy dynamic programming. It can be formulated by the fuzzy network with lingustic variables and solved by the Klein algorithm. This paper focuses on a revised fuzzy shortest path algorithm and an application is discussed.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2010년도 한국컴퓨터종합학술대회논문집 Vol.37 No.1(D)
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• pp.360-365
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• 2010

In this paper, we present a distributed algorithm for detecting dynamic event regions in wireless sensor network with the consideration on energy saving. Our model is that the sensing field is monitored by a large number of randomly distributed sensors with low-power battery and limited functionality, and that the event region is dynamic with motion or changing the shape. At any time that the event happens, we need some sensors awake to detect it and to wake up its k-hop neighbors to detect further events. Scheduling for the network to save the total power-cost or to maximize the monitoring time has been studied extensively. Our scheme is that some predetermined sensors, called critical sensors are awake all the time and when the event is detected by a critical sensor the sensor broadcasts to the neighbors to check their sensing area. Then the neighbors check their area and decide whether they wake up or remain in sleeping mode with certain criteria. Our algorithm uses only 2 bit of information in communication between sensors, thus the total communication cost is low, and the speed of detecting all event region is high. We adapt two kinds of measure for the wake-up decision. With suitable threshold values, our algorithm can be applied for many applications and for the trade-off between energy saving and the efficiency of event detection.

• Advances in nano research
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• 제13권2호
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• pp.165-174
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• 2022

In the present study, a hybrid model of artificial neural network (ANN) and internet of things (IoT) is proposed to overcome the difficulties in deriving governing equations and numerical solutions of the dynamical behavior of the nano-systems. Nano-structures manifest size-dependent behavior in response to static and dynamic loadings. Nonlocal and length-scale parameters alongside with other geometrical, loading and material parameters are taken as input parameters of an ANN to observe the natural frequency and damping behavior of micro sensors made from nanocomposite material with piezoelectric layers. The behavior of a micro-beam is simulated using famous numerical methods in literature under base vibrations. The ANN was further trained to correlate the output vibrations to the base vibration. Afterwards, using IoT, the electrical potential conducted in the sensors are collected and converted to numerical data in an embedded mini-computer and transferred to a server for further calculations and decision by ANN. The ANN calculates the base vibration behavior with is crucial in mechanical systems. The speed and accuracy of the ANN in determining base excitation behavior are the strengths of this network which could be further employed by engineers and scientists.

• 대한전자공학회논문지TC
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• 제47권11호
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• pp.59-68
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• 2010

본 논문은 보상함수 수정을 통해 보다 완벽한 DSA(Dynamic Spectrum Access)를 수행하는 새로운 방법을 제시하였다. POMDP(Partially Observable Markov Decision Process)는 미래의 스펙트럼 상태를 예측하는데 사용되는 알고리즘으로서, 그 중 보상함수는 스펙트럼을 예측하는데 있어 가장 중요한 부분이다. 그러나 보상함수는 Busy 및 Idle의 두 가지 상태만 갖고 있기 때문에 채널에서 충돌이 발생하게 되면 보상함수는 Busy를 반환함으로써 2차 사용자의 성능을 감소시키게 된다. 따라서 본 논문에서는 기존의 Busy를 Busy 및 Collision 의 두 상태로 구분하였고, 이렇게 추가된 Collision 상태를 통해 2차 사용자의 채널 접근 기회를 보다 향상시킴으로서 데이터 전송율을 증대시킬 수 있도록 하였다. 또한 본 논문은 새로운 알고리즘의 신뢰도 벡터를 수학적으로 분석하였다. 마지막으로 시뮬레이션 결과를 통해 개선된 보상함수의 성능을 검증하고, 이를 통해 새로운 알고리즘이 CR 네트워크에서 2차 사용자의 성능을 향상시킬 수 있음을 보인다.

• 한국통신학회논문지
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• 제36권8A호
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• pp.712-722
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• 2011

Wireless body area network (WBAN)은 인체 주변 영역에서의 통신서비스를 제공한다. WBAN 서비스는 인체 내부에 이식된 의료 응용을 위한 MICS 주파수 대역과 의료 응용과 consumer electronics (CE) 응용 분야 모두를 제공할 수 있는 ISM 주파수 대역에서의 서비스로 이루어지기 때문에 WBAN을 위한 MAC 프로토콜은 의료 응용과 CE 응용간의 상이한 특징과 유연성 (flexibility)을 고려하여 설계되어야 한다. 본 논문에서는 WBAN MAC 프로토콜의 요구사항을 확인하고, WBAN의 요구사항을 만족하는 WBAN MAC 프로토콜을 제안한다. WBAN의 다양한 응용을 위한 전송 유연성을 제공하기 위해서 동적 CFP(Contention Free Period) 할당(Dynamic CFP Allocation)을 제안한다. 또한, 경쟁 기반의 긴급 의료 데이터를 발생하는 의료 응용과 때때로 대량의 데이터를 발생하는 CE 응용을 지원하기 위해서 OCDP(opportunistic contention decision period) 구간과 4-mode Opportunity period를 제안하고, 제안한 방안을 이용하여 Inactive period와 Opportunity period를 일시적으로 전환하여 사용할 수 있는 기법을 제안한다. 다양한 시뮬레이션 결과 IEEE 802.15.4 MAC 프로토콜과 제안하는 WBAN MAC 프로토콜을 비교하였을 때, WBAN 환경에서의 전송 처리량, CFP 이용율, 전송지연 측면에서 증가된 성능 결과를 얻을 수 있었다.

• 한국항해학회지
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• 제23권2호
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• pp.11-22
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• 1999

This paper is concerned with the development of a tractable model to assist liner shipping companies in the decision-making of empty container repositioning and leasing. A hybrid methodology is presented which properly accounts for the specific characteristics of empty container management. For this mathematical models are developed based on dynamic network models, covering both land and marine segment. Then a stochastic method is presented to deal with the uncertainty of the future demand and supply. Especially, the concept of opportunity cost has been introduced in order to explain interactions between the variation of the future demand and supply and the stock level at each depot.

• ETRI Journal
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• 제29권5호
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• pp.685-687
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• 2007

In this letter, we propose a new online buffer management algorithm to simultaneously provide diverse multimedia traffic services and enhance network performance. Our online approach exhibits dynamic adaptability and responsiveness to the current traffic conditions in multimedia networks. This approach can provide high buffer utilization and thereby improve packet loss performance at the time of congestion.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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• pp.505-508
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• 1995

The automatic interpretation of awake background electroencephalogram (EEG), consisting of quantitative EEG interpretation and EEG report making, has been developed by the authors based on EEG data visually inspected by an electroencephalographer (EEGer). The present study was focused on the adaptability of the automatic EEG interpretation which was accomplished by the constructive neural network with forgetting factor. The artificial neural network (ANN) was constructed so as to give the integrative decision of the EEG by using the input signals of the intermediate judgment of 13 items of the EEG. The feature of the ANN was that it adapted to any EEGer who gave visual inspection for the training data. The developed method was evaluated based on the EEG data of 57 patients. The re-trained ANN adapted to another EEGer appropriately.