• Proceedings of the Society of Korea Industrial and System Engineering Conference
• /
• 2002.05a
• /
• pp.105-111
• /
• 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.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.9
• /
• pp.1673-1679
• /
• 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.

• Journal of the military operations research society of Korea
• /
• v.18 no.2
• /
• pp.66-95
• /
• 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.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.06d
• /
• pp.360-365
• /
• 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
• /
• v.13 no.2
• /
• pp.165-174
• /
• 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.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.47 no.11
• /
• pp.59-68
• /
• 2010

In this paper, we present a new method to complete Dynamic Spectrum Access by modifying the reward function. Partially Observable Markov Decision Process (POMDP) is an eligible algorithm to predict the upcoming spectrum opportunity. In POMDP, Reward function is the last portion and very important for prediction. However, the Reward function has only two states (Busy and Idle). When collision happens in the channel, reward function indicates busy state which is responsible for the throughput decreasing of secondary user. In this paper, we focus the difference between busy and collision state. We have proposed a new algorithm for reward function that indicates an additional state of collision which brings better communication opportunity for secondary users. Secondary users properly utilize opportunities to access Primary User channels for efficient data transmission with the help of the new reward function. We have derived mathematical belief vector of the new algorithm as well. Simulation results have corroborated the superior performance of improved reward function. The new algorithm has increased the throughput for secondary user in cognitive radio network.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.8A
• /
• pp.712-722
• /
• 2011

Wireless body area network(WBAN) provide communication service in the vicinity of the body. Since WBANs utilize both MICS frequency band for implant medical applications and ISM frequency band for medical and consumer electronics(CE) applications. Therefore, MAC protocols in WBAN should be designed considering flexibility between medical and CE applications. In this paper, we identify the requirements of WBAN MAC protocols and propose a WBAN MAC protocol which satisfies the requirements. In other to provide transmission flexibility for various applications. we present the dynamic CFP allocation and opportunity period. Extensive simulation result show that the proposed protocol achieves improved throughput and latency in WEAN environment cimpared with IEEE 802.15.4.

• Journal of the Korean Institute of Navigation
• /
• v.23 no.2
• /
• pp.11-22
• /
• 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
• /
• v.29 no.5
• /
• pp.685-687
• /
• 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
• /
• 1995.10a
• /
• pp.505-508
• /
• 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.