• Journal of Energy Engineering
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• v.12 no.4
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• pp.309-319
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• 2003

The main purpose of this paper is to present a simulation model for assessing the impacts of a variable speed wind turbine (VSWT) on the distribution network and perform a simulation analysis of volt-age profiles and harmonics along the wind turbine installed feeder using the presented model. The modeled wind energy conversion system consists of a fixed pitch wind turbine and a permanent-magnet synchronous generator, in which a controllable power electronics inverter performs variable speed operation and reactive power output control. Impact analysis on voltage profiles and harmonics of a VSWT-installed distribution feeder is addressed and simulated in terms of steady state and dynamic behaviors. Various capacities and different modes of variable speed wind turbines are simulated and investigated. Case studies demonstrate how feeder voltages are influenced by capacity and control modes of wind turbines and changes in wind speed under various network conditions, and show harmonic impacts on the feeder. Modeling and simulation analysis is based on PSCAD/EMTDC a software package.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.251-254
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• 2002

In the design of mobile wireless communication system, the location of BTS(Base Transciver Stations), RSC(Base Station Controllers), and MSC(Mobile Switching Center) is one of the most important parameters. Designing wireless communication system, the cost of equipment is need to be made low by combining various, complex parameters. We can solve this problem by combinatorial optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been extensively used for global optimization. This paper shows the four kind of algorithms which are applied to the location optimization of BTS, BSC, and MSC in designing mobile communication system and then we compare with these algorithms. And also we analyze the experimental results and shows the optimization process of these algorithms. As a the channel of a CDMA system is shared among several users, the receivers face the problem of multiple-access interference (MAI). Also, the multipath scenario leads to intersymbol interference (ISI). Both components are undesired, but unlike the additive noise process, which is usually completely unpredictable, their space-time structure helps to estimate and remove them.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.233-239
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• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.683-691
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• 2000

In this paper, we proposed the cell multiplexer using Hopfield neural network and the bandwidth predictor using the backpropagation neural network in order to make an accurate call setup decision. The cell multiplexer controls heterogeneous traffic and the bandwidth predictor estimates minimum bandwidth which satisfies traffic's QoS and maximizes throughput in network. Also, a novel connection admission controller decides on connection setup using the predicted bandwidth from bandwidth predictor and available bandwidth in networks. And then, we proposed a fuzzy traffic policer, when traffic sources violate the contract, takes an appropriate action and aim proved traffic shaper, which controls burstness which is one of key characteristics in multimedia traffic. We simulated the proposed controller. Simulation results show that the proposed controller outperforms existing controller.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.85-90
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• 2014

We realized a wireless multiple integrated laser engagement system composed of personal area network using Zigbee. The wireless laser detector had function of analog signal processor, decoder and wireless communication. However, it should consume low power and be small and light in order to be attached to a soldier's body. The decoder was realized in software to be small and light. We induced low power consumption as reducing the load of system using a narrow band optical filter. The fabricated wireless laser detector functioned well in optically noisy environment. Although the communication to the player unit through the wireless personal area network was dependent on the attachment place it was perfectly worked with transmission power of -40.2dBm or more.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.443-450
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• 2017

Nowadays, Power Line Communication (PLC) is gaining high attention from industry and electric supply companies for the services like demand response, demand side management and Advanced Metering Infrastructure (AMI). The reliable services to consumers using PLC can be provided by utilizing an efficient PLC channel for which sophisticated channel modeling is very important. This paper presents characterization of a Low Voltage (LV) access network for Narrowband Power Line Communications (NB-PLC) using transmission line (TL) theory and a Simulink model. The TL theory analysis not only includes the constant parameters but frequency selectivity is also introduced in these parameters such as resistance, conductance and impedances. However, the proposed Simulink channel model offers an analysis and characterization of capacitive coupler, network impedance and channel transfer function for NB-PLC. Analysis of analytical and simulated results shows a close agreement of the channel transfer function. In the absence of a standardized NBPLC channel model, this research work can prove significant in improving the efficiency and accuracy of NB-PLC communication transceivers for Smart Grid communications.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.8
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• pp.1269-1277
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• 2008

Ships at sea cannot exchange data among them easily so far. Basically voice-oriented communication systems are the main methods, some of them utilize the HF radio systems at lower bit rates, and for higher bit rates, the Inmarsat or VSAT are adopted. None of them are used widely because of lower qualities and higher costs. There exist many technical and economical limits to have the Internet service just like on land such as the WWW service. In order to achieve the improved transmission rates of the maritime communication networks at farther sea, MANET(Mobile Ad Hoc Network) is one of the most practical models. In this paper, a new routing protocol named EZR (Expansive Search Zone Routing Protocol) is proposed, which is based on SANET (Ship Ad Hoc Network) model that has some different features from MANET and VANET (Vehicular Ad Hoc Network). The search zone for the shortest path is firstly found by EZR. If no path is searched in the zone, the zone is expanded according to the rule of EZR. The zone-expanding and path-searching procedures are repeated until the path is found out. The performance of EZR is evaluated and compared with LAR protocol which is one of the most typical routing protocols based on geographical information. The simulated results show that EZR is much better than LAR at sea environments in terms of routing success rate, route optimality, and a single index of performance combined the previous two metrics.

• Nuclear Engineering and Technology
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• v.31 no.2
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• pp.192-201
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• 1999

This paper proposes an improved signal processing strategy for accurate feedwater flowrate estimation in nuclear power plants. It is generally known that ∼2% thermal power errors occur due to fouling Phenomena in feedwater flowmeters. In the strategy Proposed, the noises included in feedwater flowrate signal are classified into rapidly varying noises and gradually varying noises according to the characteristics in a frequency domain. The estimation precision is enhanced by introducing a low pass filter with the wavelet analysis against rapidly varying noises, and an autoassociative neural network which takes charge of the correction of only gradually varying noises. The modified multivariate stratification sampling using the concept of time stratification and MAXIMIN criteria is developed to overcome the shortcoming of a general random sampling. In addition the multi-stage robust training method is developed to increase the quality and reliability of training signals. Some validations using the simulated data from a micro-simulator were carried out. In the validation tests, the proposed methodology removed both rapidly varying noises and gradually varying noises respectively in each de-noising step, and 5.54% root mean square errors of initial noisy signals were decreased to 0.674% after de-noising. These results indicate that it is possible to estimate the reactor thermal power more elaborately by adopting this strategy.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.9
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• pp.923-928
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• 2016

The various technologies related to the monitoring human health in real-time for the emergency situations are developing these days. Mostly the human pulse is used for measuring as the vital signs so far, but the EEG became a major research trend now. However, there are some problems measuring and sending EEG signals of all the people walking down the street to the dedicated server. Especially, there are some restrictions for collecting and sending EEG signals in 2-dimensional space in real-time. Therefore, I suggests an efficient network model using 3-dimensional space of drones to avoid the restrictions. The models are designed, simulated, and evaluated with the Opnet simulator.